Data Scientist Jobs are in high demand due to the exponential growth of data. Companies are seeking skilled professionals to analyze data and provide insights to make informed business decisions. A career in data science offers opportunities to work with large datasets, cutting-edge technology, and a competitive salary. Start your job search today and become a part of this exciting field.
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Big Data Laser Analyst Description - Job Summary • We are seeking a highly analytical, business-oriented Data Analyst to support the Print Supplies business. In this role, you will translate consumer and enterprise print telemetry into trusted metrics, dashboards, and actionable insights, with a primary focus on laser printer data. You will partner closely with data engineers and data scientists to improve data reliability, define KPI and metric semantics, and influence cross-functional decisions through clear data storytelling. Responsibilities • Own laser print telemetry business insights for the Print Supplies organization, from problem framing and metric definition through analysis, visualization, and executive-ready recommendations. • Partner with stakeholders to clarify goals, translate business questions into analytical requirements, define critical KPIs, and deliver insights that drive decisions. • Provide consultative support and ad hoc analyses with clear hypotheses, methods, and assumptions; produce reusable queries, datasets, and shareable outputs with documented limitations. • Collaborate with internal and external partners to align on telemetry instrumentation, data collection methodology, and platform differences to ensure consistent interpretation across printer platforms. • Investigate data quality issues (completeness, accuracy, timeliness), perform root-cause analysis across pipelines and sources, and communicate impacts and remediation paths with appropriate caveats. • Enable self-service analytics by documenting dashboards and KPI definitions, and coach users on correct interpretation and common pitfalls. • Design and maintain measurement frameworks (e.g., adoption, usage, retention, share, funnel/driver analyses); when applicable, support experiment or pre/post evaluation and interpret results for stakeholders. • Create clear narratives through written summaries, presentations, and recurring reporting that highlight trends, drivers, risks, and recommended actions for leadership and partner teams. • Provide guidance and mentoring to less- experienced staff members. • Solve difficult and complex problems with a fresh perspective, demonstrating good judgment in selecting creative solutions and managing projects independently. • Lead moderate to high complexity projects, delivering professionally written reports, and supports the realization of operational and strategic plans. Education & Experience Recommended • Four-year or Graduate Degree in Mathematics, Statistics, Economics, Computer Science, or any other related discipline or commensurate work experience or demonstrated competence. • Typically has 4-7 years of work experience, preferably in data analytics, database management, statistical analysis, or a related field or an advanced degree with 3-5 years of work experience. Preferred Certifications • Programming Language/s Certification (SQL, Python, or similar) Knowledge & Skills • Analytics: exploratory analysis, root-cause analysis, and KPI design • SQL: complex joins, CTEs, window functions, query performance optimization • Python (and/or PySpark) for analysis, data validation, and automation. Familiar with VSCode and Databricks Ideally • Ability to interpret telemetry and pipeline outputs in business context, including communicating uncertainty and known limitations • Comfort working across multiple data sources/layers and explaining differences in source-of-truth, grain, and transformations • Comfort with modern analytics tooling (including AI-assisted development) while maintaining reproducibility and reviewable outputs • Dashboarding & data visualization: Power BI, Tableau, Qlik, advanced excel / PowerPoint or similar; ability to build stakeholder-ready reporting • Data quality and governance: profiling, anomaly detection, metric validation, and documentation • Strong documentation habits for metric definitions, data lineage, and stakeholder guidance; familiarity with version control (e.g., Git) a plus. Familiar with Jira and Confluence. • Applied statistics: sampling, confidence intervals, and basic experiment/pre-post evaluation Cross-Org Skills • Effective Communication • Results Orientation • Learning Agility • Digital Fluency • Customer Centricity • Collaboration across technical and non-technical teams Impact & Scope • Impacts function by providing analytics and data quality validation that supports business-critical reporting and stakeholder decision-making for laser telemetry KPIs • Serves as a key point of contact for laser telemetry interpretation and investigation requests, partnering across teams to drive consistent definitions and reliable use of outputs Complexity • Responds to moderately complex issues within established guidelines. Disclaimer • This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management. Salary The pay range for this role is $83,000 to $127,800 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Data & Information Technology Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - No Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
10/07/2026
Full time
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Big Data Laser Analyst Description - Job Summary • We are seeking a highly analytical, business-oriented Data Analyst to support the Print Supplies business. In this role, you will translate consumer and enterprise print telemetry into trusted metrics, dashboards, and actionable insights, with a primary focus on laser printer data. You will partner closely with data engineers and data scientists to improve data reliability, define KPI and metric semantics, and influence cross-functional decisions through clear data storytelling. Responsibilities • Own laser print telemetry business insights for the Print Supplies organization, from problem framing and metric definition through analysis, visualization, and executive-ready recommendations. • Partner with stakeholders to clarify goals, translate business questions into analytical requirements, define critical KPIs, and deliver insights that drive decisions. • Provide consultative support and ad hoc analyses with clear hypotheses, methods, and assumptions; produce reusable queries, datasets, and shareable outputs with documented limitations. • Collaborate with internal and external partners to align on telemetry instrumentation, data collection methodology, and platform differences to ensure consistent interpretation across printer platforms. • Investigate data quality issues (completeness, accuracy, timeliness), perform root-cause analysis across pipelines and sources, and communicate impacts and remediation paths with appropriate caveats. • Enable self-service analytics by documenting dashboards and KPI definitions, and coach users on correct interpretation and common pitfalls. • Design and maintain measurement frameworks (e.g., adoption, usage, retention, share, funnel/driver analyses); when applicable, support experiment or pre/post evaluation and interpret results for stakeholders. • Create clear narratives through written summaries, presentations, and recurring reporting that highlight trends, drivers, risks, and recommended actions for leadership and partner teams. • Provide guidance and mentoring to less- experienced staff members. • Solve difficult and complex problems with a fresh perspective, demonstrating good judgment in selecting creative solutions and managing projects independently. • Lead moderate to high complexity projects, delivering professionally written reports, and supports the realization of operational and strategic plans. Education & Experience Recommended • Four-year or Graduate Degree in Mathematics, Statistics, Economics, Computer Science, or any other related discipline or commensurate work experience or demonstrated competence. • Typically has 4-7 years of work experience, preferably in data analytics, database management, statistical analysis, or a related field or an advanced degree with 3-5 years of work experience. Preferred Certifications • Programming Language/s Certification (SQL, Python, or similar) Knowledge & Skills • Analytics: exploratory analysis, root-cause analysis, and KPI design • SQL: complex joins, CTEs, window functions, query performance optimization • Python (and/or PySpark) for analysis, data validation, and automation. Familiar with VSCode and Databricks Ideally • Ability to interpret telemetry and pipeline outputs in business context, including communicating uncertainty and known limitations • Comfort working across multiple data sources/layers and explaining differences in source-of-truth, grain, and transformations • Comfort with modern analytics tooling (including AI-assisted development) while maintaining reproducibility and reviewable outputs • Dashboarding & data visualization: Power BI, Tableau, Qlik, advanced excel / PowerPoint or similar; ability to build stakeholder-ready reporting • Data quality and governance: profiling, anomaly detection, metric validation, and documentation • Strong documentation habits for metric definitions, data lineage, and stakeholder guidance; familiarity with version control (e.g., Git) a plus. Familiar with Jira and Confluence. • Applied statistics: sampling, confidence intervals, and basic experiment/pre-post evaluation Cross-Org Skills • Effective Communication • Results Orientation • Learning Agility • Digital Fluency • Customer Centricity • Collaboration across technical and non-technical teams Impact & Scope • Impacts function by providing analytics and data quality validation that supports business-critical reporting and stakeholder decision-making for laser telemetry KPIs • Serves as a key point of contact for laser telemetry interpretation and investigation requests, partnering across teams to drive consistent definitions and reliable use of outputs Complexity • Responds to moderately complex issues within established guidelines. Disclaimer • This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management. Salary The pay range for this role is $83,000 to $127,800 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Data & Information Technology Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - No Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
This role requires the ability to work lawfully in the U.S. without employment-based immigration sponsorship, now or in the future. Are you ready to develop data-driven solutions that tackle Spectrum's business challenges? As a Data Scientist VI, you will utilize your analytical, statistical, and programming skills to clean, aggregate, and analyze large data sets, interpreting the results to drive impactful decisions for the organization, as well as mentoring more junior members of the team. How You'll Make an Impact Visualize and report data findings creatively in a variety of visual formats that appropriately provide insight to the stakeholders and explain the importance of patterns in the data Lead large-scale exploratory data analyses for new data sources or new uses for existing data sources Collaborate with leadership and other stakeholders on project strategy, direction and changes Use time and resources effectively, prioritizing work, establishing and meeting timelines without oversight, and delivering multiple tasks at the same time Close technical debts and visualizes technology roadmaps Provide guidance and support to junior staff during response efforts Apply appropriate level of data maintenance, data quality control and validation of code, tools, and models Mentor Data Scientists I-IV Working Conditions Office environment QUALIFICATIONS: What You'll Bring to Spectrum Required Qualifications Education Bachelor's degree in computer science, statistics, operations research and/or equivalent combination of education and experience Experience 4+ years of experience in data manipulation and statistical modeling as a Scientist, Consultant, Architect, DBA, or Engineer 4+ years of programming experience Skills Ability to perform involved and independent research and analysis, effectively create and present data insights and recommendations to key stakeholders independently Demonstrated practical ability to determine where to invest time, synthesize actionable findings across diverse assignments, and present findings to audiences with diverse agendas and varying levels of technical expertise Extensive knowledge of core data science and machine learning principles and ability to identify and apply the appropriate techniques with minimal oversight Proficient in at least one data science toolkit such as Python or R and able to learn additional languages and functionality Comprehensive level SQL skills Experience with large data sets and proficient with big data tools such as Spark and Hive Familiarity with broader cloud-based infrastructure and ability to troubleshoot issues with guidance In-depth knowledge of advanced mathematical and statistical concepts and the ability to learn and apply new techniques independently Mastery of development of data tools and models, scripting, analysis and ETL, and ability to synthesize complex code Basic understanding of data architecture, data warehouse and data marts Strong command of statistical techniques and machine learning algorithms Preferred Qualifications Expert-level experience designing, developing, and maintaining scalable data pipelines and ETL/ELT workflows. Proficient on data orchestration tooling like Airflow or AWS Step Functions. • Strong programming skills in Python and Scala with experience optimizing complex queries and data transformations for performance and cost efficiency • Deep understanding of data modeling, distributed systems, and performance optimization for Big Data. • The ability to deliver work at a steady, predictable pace to achieve commitments, deliver complete solutions but release them in small batches, and identify and negotiate important tradeoffs. • Strong problem solver who ensures systems are built with longevity and creates innovative ways to resolve issues. • Experienced in production operations of developed software, software development methodologies, and applying appropriate software design patterns to the situation BDA324 4 BDA324 2026 Here, our employees don't just have jobs, they're building careers. That's why we offer a comprehensive pay and benefits package that rewards employees for their contributions to our success, supporting all aspects of their well-being at every stage of life. A qualified applicant's criminal history, if any, will be considered in a manner consistent with applicable laws, including local ordinances. This job posting will remain open until 2026-10-:00 PM (UTC) and will be extended if necessary. The base pay for this position generally is between $98,900.00 and $175,300.00. The actual compensation offered will carefully consider a wide range of factors, including your skills, qualifications, experience, and location. We comply with local wage minimums and also, certain positions are eligible for additional forms of other incentive-based compensation such as bonuses. Get to Know Us Charter Communications provides superior communication and entertainment products for residential and business customers through the Spectrum brand. Our offerings include Spectrum Internet , TV, Mobile and Voice. Beyond our connectivity solutions, we also provide local news, programming and regional sports via Spectrum Networks and multiscreen advertising solutions via Spectrum Reach. When you join our team, you'll be keeping our customers connected to what matters most in 41 states across the U.S. Watch this video to learn more. Grow Your Career Here We're committed to growing a workforce that reflects the customers and communities we serve - providing opportunities for employment and advancement to all team members. Spectrum is an Equal Opportunity Employer, including job seekers with disabilities and veterans. Learn about Life at Spectrum.
10/07/2026
Full time
This role requires the ability to work lawfully in the U.S. without employment-based immigration sponsorship, now or in the future. Are you ready to develop data-driven solutions that tackle Spectrum's business challenges? As a Data Scientist VI, you will utilize your analytical, statistical, and programming skills to clean, aggregate, and analyze large data sets, interpreting the results to drive impactful decisions for the organization, as well as mentoring more junior members of the team. How You'll Make an Impact Visualize and report data findings creatively in a variety of visual formats that appropriately provide insight to the stakeholders and explain the importance of patterns in the data Lead large-scale exploratory data analyses for new data sources or new uses for existing data sources Collaborate with leadership and other stakeholders on project strategy, direction and changes Use time and resources effectively, prioritizing work, establishing and meeting timelines without oversight, and delivering multiple tasks at the same time Close technical debts and visualizes technology roadmaps Provide guidance and support to junior staff during response efforts Apply appropriate level of data maintenance, data quality control and validation of code, tools, and models Mentor Data Scientists I-IV Working Conditions Office environment QUALIFICATIONS: What You'll Bring to Spectrum Required Qualifications Education Bachelor's degree in computer science, statistics, operations research and/or equivalent combination of education and experience Experience 4+ years of experience in data manipulation and statistical modeling as a Scientist, Consultant, Architect, DBA, or Engineer 4+ years of programming experience Skills Ability to perform involved and independent research and analysis, effectively create and present data insights and recommendations to key stakeholders independently Demonstrated practical ability to determine where to invest time, synthesize actionable findings across diverse assignments, and present findings to audiences with diverse agendas and varying levels of technical expertise Extensive knowledge of core data science and machine learning principles and ability to identify and apply the appropriate techniques with minimal oversight Proficient in at least one data science toolkit such as Python or R and able to learn additional languages and functionality Comprehensive level SQL skills Experience with large data sets and proficient with big data tools such as Spark and Hive Familiarity with broader cloud-based infrastructure and ability to troubleshoot issues with guidance In-depth knowledge of advanced mathematical and statistical concepts and the ability to learn and apply new techniques independently Mastery of development of data tools and models, scripting, analysis and ETL, and ability to synthesize complex code Basic understanding of data architecture, data warehouse and data marts Strong command of statistical techniques and machine learning algorithms Preferred Qualifications Expert-level experience designing, developing, and maintaining scalable data pipelines and ETL/ELT workflows. Proficient on data orchestration tooling like Airflow or AWS Step Functions. • Strong programming skills in Python and Scala with experience optimizing complex queries and data transformations for performance and cost efficiency • Deep understanding of data modeling, distributed systems, and performance optimization for Big Data. • The ability to deliver work at a steady, predictable pace to achieve commitments, deliver complete solutions but release them in small batches, and identify and negotiate important tradeoffs. • Strong problem solver who ensures systems are built with longevity and creates innovative ways to resolve issues. • Experienced in production operations of developed software, software development methodologies, and applying appropriate software design patterns to the situation BDA324 4 BDA324 2026 Here, our employees don't just have jobs, they're building careers. That's why we offer a comprehensive pay and benefits package that rewards employees for their contributions to our success, supporting all aspects of their well-being at every stage of life. A qualified applicant's criminal history, if any, will be considered in a manner consistent with applicable laws, including local ordinances. This job posting will remain open until 2026-10-:00 PM (UTC) and will be extended if necessary. The base pay for this position generally is between $98,900.00 and $175,300.00. The actual compensation offered will carefully consider a wide range of factors, including your skills, qualifications, experience, and location. We comply with local wage minimums and also, certain positions are eligible for additional forms of other incentive-based compensation such as bonuses. Get to Know Us Charter Communications provides superior communication and entertainment products for residential and business customers through the Spectrum brand. Our offerings include Spectrum Internet , TV, Mobile and Voice. Beyond our connectivity solutions, we also provide local news, programming and regional sports via Spectrum Networks and multiscreen advertising solutions via Spectrum Reach. When you join our team, you'll be keeping our customers connected to what matters most in 41 states across the U.S. Watch this video to learn more. Grow Your Career Here We're committed to growing a workforce that reflects the customers and communities we serve - providing opportunities for employment and advancement to all team members. Spectrum is an Equal Opportunity Employer, including job seekers with disabilities and veterans. Learn about Life at Spectrum.
Job Family: Data Science Consulting Travel Required: Up to 10% Clearance Required: Ability to Obtain Public Trust What You Will Do: Guidehouse is seeking a Data Scientist to join our AI & Data Defense and Security Segment, where the individual will collect and analyze data to identify trends, develop visualizations in support of organizational and mission goals, and support decision-making for large-scale programs within the Department of Homeland Security (DHS). Responsibilities include, but are not limited to: Design and develop data visualization and dashboard solutions to provide required analytics insights (Power BI) Collecting, cleaning, and analyzing data using a variety of methods and tools, such as R Identifying and creating additional data visualization capabilities, as needed Ensuring data governance and quality assurance standards are met Conducting data validation and remediation using tools such as R and Excel Analyzing current process and identifying potential improvements Working with team members to summarize and report on business process improvements to include gaps in current processes and initiatives to improve processes for an organization Organizing and leading client meetings, including scheduling meetings; drafting and delivering agendas and meeting minutes; providing and archiving required documentation; and documenting, tracking, and following-up on action items Summarizing and presenting information and reports to the team and make recommendations (both oral and written) What You Will Need: Must be able to OBTAIN and MAINTAIN a Federal or DHS "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred Bachelors Degree At least THREE (3) years of experience in consulting, data analytics, or project management What Would Be Nice To Have: Active DHS Public Trust Law Enforcement experience Data visualization tools such as Power BI Good critical thinking skills, writing skills, and communication skills Experience in business analysis Experience connecting visualization to various types of data sources Experience developing training materials Experience with process improvement Database optimization Monitoring program operations to ensure compliance with federal regulations Knowledge of ETL/ELT processes and tools for data integration, such as: Databricks, Snowflake, Azure Data Factory, Microsoft SQL Server tools (SSIS, SSMS, SSAS, SSRS), Azure Synapse Analytics Proficiency in querying data using SQL and experience optimizing SQL query performance for large datasets What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Position may be eligible for a discretionary variable incentive bonus Parental Leave and Adoption Assistance 401(k) Retirement Plan Basic Life & Supplemental Life Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts Short-Term & Long-Term Disability Student Loan PayDown Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Corporate Sponsored Events & Community Outreach Emergency Back-Up Childcare Program Mobility Stipend About Guidehouse Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains or . Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact . Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.
10/05/2026
Full time
Job Family: Data Science Consulting Travel Required: Up to 10% Clearance Required: Ability to Obtain Public Trust What You Will Do: Guidehouse is seeking a Data Scientist to join our AI & Data Defense and Security Segment, where the individual will collect and analyze data to identify trends, develop visualizations in support of organizational and mission goals, and support decision-making for large-scale programs within the Department of Homeland Security (DHS). Responsibilities include, but are not limited to: Design and develop data visualization and dashboard solutions to provide required analytics insights (Power BI) Collecting, cleaning, and analyzing data using a variety of methods and tools, such as R Identifying and creating additional data visualization capabilities, as needed Ensuring data governance and quality assurance standards are met Conducting data validation and remediation using tools such as R and Excel Analyzing current process and identifying potential improvements Working with team members to summarize and report on business process improvements to include gaps in current processes and initiatives to improve processes for an organization Organizing and leading client meetings, including scheduling meetings; drafting and delivering agendas and meeting minutes; providing and archiving required documentation; and documenting, tracking, and following-up on action items Summarizing and presenting information and reports to the team and make recommendations (both oral and written) What You Will Need: Must be able to OBTAIN and MAINTAIN a Federal or DHS "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred Bachelors Degree At least THREE (3) years of experience in consulting, data analytics, or project management What Would Be Nice To Have: Active DHS Public Trust Law Enforcement experience Data visualization tools such as Power BI Good critical thinking skills, writing skills, and communication skills Experience in business analysis Experience connecting visualization to various types of data sources Experience developing training materials Experience with process improvement Database optimization Monitoring program operations to ensure compliance with federal regulations Knowledge of ETL/ELT processes and tools for data integration, such as: Databricks, Snowflake, Azure Data Factory, Microsoft SQL Server tools (SSIS, SSMS, SSAS, SSRS), Azure Synapse Analytics Proficiency in querying data using SQL and experience optimizing SQL query performance for large datasets What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Position may be eligible for a discretionary variable incentive bonus Parental Leave and Adoption Assistance 401(k) Retirement Plan Basic Life & Supplemental Life Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts Short-Term & Long-Term Disability Student Loan PayDown Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Corporate Sponsored Events & Community Outreach Emergency Back-Up Childcare Program Mobility Stipend About Guidehouse Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains or . Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact . Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.
Job Family: Data Science Consulting Travel Required: Up to 10% Clearance Required: Active Public Trust What You Will Do: The Border Security Data Scientist will join a dynamic team supporting U.S Federal border security customers. In this role, the candidate will collect, transform, integrate, and analyze data to. develop integrated data models, generate reports and analyses for key senior leaders and deploy dynamic analytical solutions. Develop integrated data pipelines and models to support law enforcement operations Develop and maintain data governance documentation, tools, and templates. Coordinate with non-technical users to gather requirements. Request, document, report, and analyze data, and where applicable, create tools and resources to support data and reporting. Support key mission clients within the Washington DC Metro region at client sites. We are actively hiring for this role at multiple levels (Associate, Senior, and Lead) to support ongoing and upcoming federal client work across CBP. Candidates will be considered and leveled based on experience, technical capabilities, and overall alignment to project needs. What You Will Need: An ACTIVE and MAINTAINED CBP PUBLIC TRUST or An ACTIVE and MAINTAINED "TOP SECRET" Federal or DoD security clearance. Bachelors Degree Experience in performing data analysis, mining and/or architecture using tools such as SQL, Python, R, etc. Experience developing transformative data integration solutions that transform border, national security or law enforcement data Experience performing modelling and/or simulation analysis What Would Be Nice To Have: Proficiency in querying and mining large classified data sets Proficiency in data wrangling and analysis using Python. Proficiency with COTS tools such as DataRobot, Senzing and others Experience developing bespoke analytical tools for law enforcement analysis Direct Experience supporting the National Targeting Center or similar National Security analysis fusion centers What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Position may be eligible for a discretionary variable incentive bonus Parental Leave and Adoption Assistance 401(k) Retirement Plan Basic Life & Supplemental Life Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts Short-Term & Long-Term Disability Student Loan PayDown Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Corporate Sponsored Events & Community Outreach Emergency Back-Up Childcare Program Mobility Stipend About Guidehouse Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains or . Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact . Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.
10/05/2026
Full time
Job Family: Data Science Consulting Travel Required: Up to 10% Clearance Required: Active Public Trust What You Will Do: The Border Security Data Scientist will join a dynamic team supporting U.S Federal border security customers. In this role, the candidate will collect, transform, integrate, and analyze data to. develop integrated data models, generate reports and analyses for key senior leaders and deploy dynamic analytical solutions. Develop integrated data pipelines and models to support law enforcement operations Develop and maintain data governance documentation, tools, and templates. Coordinate with non-technical users to gather requirements. Request, document, report, and analyze data, and where applicable, create tools and resources to support data and reporting. Support key mission clients within the Washington DC Metro region at client sites. We are actively hiring for this role at multiple levels (Associate, Senior, and Lead) to support ongoing and upcoming federal client work across CBP. Candidates will be considered and leveled based on experience, technical capabilities, and overall alignment to project needs. What You Will Need: An ACTIVE and MAINTAINED CBP PUBLIC TRUST or An ACTIVE and MAINTAINED "TOP SECRET" Federal or DoD security clearance. Bachelors Degree Experience in performing data analysis, mining and/or architecture using tools such as SQL, Python, R, etc. Experience developing transformative data integration solutions that transform border, national security or law enforcement data Experience performing modelling and/or simulation analysis What Would Be Nice To Have: Proficiency in querying and mining large classified data sets Proficiency in data wrangling and analysis using Python. Proficiency with COTS tools such as DataRobot, Senzing and others Experience developing bespoke analytical tools for law enforcement analysis Direct Experience supporting the National Targeting Center or similar National Security analysis fusion centers What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Position may be eligible for a discretionary variable incentive bonus Parental Leave and Adoption Assistance 401(k) Retirement Plan Basic Life & Supplemental Life Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts Short-Term & Long-Term Disability Student Loan PayDown Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Corporate Sponsored Events & Community Outreach Emergency Back-Up Childcare Program Mobility Stipend About Guidehouse Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains or . Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact . Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.
Job Family: Data Science Consulting Travel Required: Up to 10% Clearance Required: Active Secret What You Will Do: Guidehouse is seeking a Senior Data Analytics Consultant who will provide data solutions (analysis, data engineering, data science etc.) to a Department of Defense client. You will be a part of a multi-disciplinary, high-impact team supporting the client achieve and infrastructure excellence. The ideal candidate will perform technical tasks that include, but are not limited to, building data pipelines, developing visualizations, and building predictive models. These tasks will involve using advanced tools and technologies such as Python, R, SQL, and data visualization platforms like Workshop and Slate within Palantir Foundry. The consultant will also be responsible for ensuring data integrity and security, adhering to best practices in data management, and staying updated with the latest trends in data analytics. Experience with machine learning algorithms and statistical analysis will be highly advantageous. What You Will Need: An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance Bachelor's Degree THREE (3) or more years of experience as a data scientist, data analyst or data engineer What Would Be Nice To Have: Knowledge of infrastructure and MILCON Proficiency in programming languages such as Python or R Excellent problem-solving skills and attention to detail Strong communication and collaboration skills, with the ability to work effectively in a team environment Experience with design and build of ETL programs, interfaces, and data reconciliation processes Ability to effectively communicate with all levels of staff within an organization What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Position may be eligible for a discretionary variable incentive bonus Parental Leave and Adoption Assistance 401(k) Retirement Plan Basic Life & Supplemental Life Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts Short-Term & Long-Term Disability Student Loan PayDown Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Corporate Sponsored Events & Community Outreach Emergency Back-Up Childcare Program Mobility Stipend About Guidehouse Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains or . Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact . Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.
10/05/2026
Full time
Job Family: Data Science Consulting Travel Required: Up to 10% Clearance Required: Active Secret What You Will Do: Guidehouse is seeking a Senior Data Analytics Consultant who will provide data solutions (analysis, data engineering, data science etc.) to a Department of Defense client. You will be a part of a multi-disciplinary, high-impact team supporting the client achieve and infrastructure excellence. The ideal candidate will perform technical tasks that include, but are not limited to, building data pipelines, developing visualizations, and building predictive models. These tasks will involve using advanced tools and technologies such as Python, R, SQL, and data visualization platforms like Workshop and Slate within Palantir Foundry. The consultant will also be responsible for ensuring data integrity and security, adhering to best practices in data management, and staying updated with the latest trends in data analytics. Experience with machine learning algorithms and statistical analysis will be highly advantageous. What You Will Need: An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance Bachelor's Degree THREE (3) or more years of experience as a data scientist, data analyst or data engineer What Would Be Nice To Have: Knowledge of infrastructure and MILCON Proficiency in programming languages such as Python or R Excellent problem-solving skills and attention to detail Strong communication and collaboration skills, with the ability to work effectively in a team environment Experience with design and build of ETL programs, interfaces, and data reconciliation processes Ability to effectively communicate with all levels of staff within an organization What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Position may be eligible for a discretionary variable incentive bonus Parental Leave and Adoption Assistance 401(k) Retirement Plan Basic Life & Supplemental Life Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts Short-Term & Long-Term Disability Student Loan PayDown Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Corporate Sponsored Events & Community Outreach Emergency Back-Up Childcare Program Mobility Stipend About Guidehouse Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains or . Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact . Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.
Job Description: Established nearly two centuries ago, FM is a leading mutual insurance company whose capital, scientific research capability and engineering expertise are solely dedicated to property risk management and the resilience of its policyholder-owners. These owners, who share the belief that the majority of property loss is preventable, represent many of the world's largest organizations, including one of every four Fortune 500 companies. They work with FM to better understand the hazards that can impact their business continuity to make cost-effective risk management decisions, combining property loss prevention with insurance protection. Schedule & Location Employment Type: Full-time, exempt (salaried). This role can be based out of our Norwood, MA or Johnston, RI office, with an in-office schedule of 2 days per week and flexibility to work remotely 3 days per week, dependent on business needs. Relocation assistance is not offered for this position. Job Summary FM is seeking an experienced Analytics Solution Architect to lead the design and delivery of enterprise analytics, AI, and data-driven solutions. In this role, you will work across modern data, cloud, and application platforms to build scalable, secure, and production-ready solutions that enable advanced analytics, machine learning, business intelligence, and operational decision-making. You will partner closely with business stakeholders, product owners, data scientists, engineers, and platform teams to translate business needs into technical solutions. This role requires a blend of solution architecture, analytics architecture, software engineering, cloud technologies, and AI enablement, with a focus on delivering solutions that are reliable, maintainable, and aligned with long-term business objectives. The ideal candidate combines strong architecture and engineering expertise with the ability to lead through collaboration. You will help define how data, analytics, applications, and AI capabilities are designed, integrated, deployed, governed, and supported across the enterprise while providing technical leadership on strategic initiatives. Responsibilities Lead the architecture and delivery of data, AI and business solutions by designing scalable applications, data and analytics platforms, integration frameworks, and cloud-based solutions. Partner with business stakeholders, product owners, data scientists and engineering teams to translate business needs into technical solutions, define architecture roadmaps, and drive the successful delivery of strategic initiatives. Design and operationalize AI and machine learning solutions by enabling the transition of analytical models from development into secure, scalable, and production-ready environments while ensuring reliability, maintainability, and long-term supportability. Establish architecture standards and governance to ensure scalable, secure, reliable, and maintainable solutions across data, application, and cloud platforms. Evaluate emerging technologies, architecture patterns, and AI capabilities to drive innovation, platform modernization, and improved business outcomes. Provide technical leadership by mentoring teammates, advising stakeholders, and promoting best practices in solution architecture, application development, data and AI platforms, and technology delivery. Qualifications: Minimum of 7 years of experience in Solution Architecture or related technical leadership roles, with experience delivering data, analytics, AI, and cloud-based solutions; 10+ years preferred. Solution Architecture: Experience designing and delivering scalable applications, data and analytics platforms, cloud-native solutions, and integration architectures in an enterprise environment. Advanced Analytics Enablement: Experience partnering with data science teams to design, deploy, and operationalize machine learning and AI solutions in production environments. Technical Expertise: Strong understanding of modern software development practices, cloud and data platforms, CI/CD, security, and operational support. Experience with Python, machine learning concepts, and operationalizing analytical models preferred. Effective communication: Ability to translate complex technical concepts into clear recommendations for business, technical, and senior stakeholder audiences through strong written, verbal, and interpersonal communication. Decision making: Demonstrated ability to evaluate priorities, assess return on investment, resolve obstacles, and make sound architecture recommendations that support business outcomes and enterprise standards. Collaboration and teamwork: Proven ability to influence cross-functional teams, mentor technical staff, build strong stakeholder relationships, and drive successful delivery of strategic initiatives. Leadership mindset: Self-directed, customer-focused professional with strong problem-solving skills and a commitment to delivering high-quality scalable Analytics and AI solutions. Education and Certifications Bachelor's degree in computer science, Information Technology, Data Analytics, Data Science, Engineering, or a related field; equivalent experience considered. Master's degree in information technology, analytics, data science, or related discipline preferred. The hiring range for this position is $121,000 - $198,000 a year. The final salary offer will vary based on geographic location, individual education, skills, and experience. The position is eligible to participate in FM's comprehensive Total Rewards program that includes an incentive plan, medical, dental and vision insurance, life and disability insurance, well-being programs, a 401(k) and pension plan, career development opportunities, tuition reimbursement, flexible work, and time off, including vacation and sick time. FM is an Equal Opportunity Employer and is committed to attracting, developing, and retaining a diverse workforce.
10/02/2026
Full time
Job Description: Established nearly two centuries ago, FM is a leading mutual insurance company whose capital, scientific research capability and engineering expertise are solely dedicated to property risk management and the resilience of its policyholder-owners. These owners, who share the belief that the majority of property loss is preventable, represent many of the world's largest organizations, including one of every four Fortune 500 companies. They work with FM to better understand the hazards that can impact their business continuity to make cost-effective risk management decisions, combining property loss prevention with insurance protection. Schedule & Location Employment Type: Full-time, exempt (salaried). This role can be based out of our Norwood, MA or Johnston, RI office, with an in-office schedule of 2 days per week and flexibility to work remotely 3 days per week, dependent on business needs. Relocation assistance is not offered for this position. Job Summary FM is seeking an experienced Analytics Solution Architect to lead the design and delivery of enterprise analytics, AI, and data-driven solutions. In this role, you will work across modern data, cloud, and application platforms to build scalable, secure, and production-ready solutions that enable advanced analytics, machine learning, business intelligence, and operational decision-making. You will partner closely with business stakeholders, product owners, data scientists, engineers, and platform teams to translate business needs into technical solutions. This role requires a blend of solution architecture, analytics architecture, software engineering, cloud technologies, and AI enablement, with a focus on delivering solutions that are reliable, maintainable, and aligned with long-term business objectives. The ideal candidate combines strong architecture and engineering expertise with the ability to lead through collaboration. You will help define how data, analytics, applications, and AI capabilities are designed, integrated, deployed, governed, and supported across the enterprise while providing technical leadership on strategic initiatives. Responsibilities Lead the architecture and delivery of data, AI and business solutions by designing scalable applications, data and analytics platforms, integration frameworks, and cloud-based solutions. Partner with business stakeholders, product owners, data scientists and engineering teams to translate business needs into technical solutions, define architecture roadmaps, and drive the successful delivery of strategic initiatives. Design and operationalize AI and machine learning solutions by enabling the transition of analytical models from development into secure, scalable, and production-ready environments while ensuring reliability, maintainability, and long-term supportability. Establish architecture standards and governance to ensure scalable, secure, reliable, and maintainable solutions across data, application, and cloud platforms. Evaluate emerging technologies, architecture patterns, and AI capabilities to drive innovation, platform modernization, and improved business outcomes. Provide technical leadership by mentoring teammates, advising stakeholders, and promoting best practices in solution architecture, application development, data and AI platforms, and technology delivery. Qualifications: Minimum of 7 years of experience in Solution Architecture or related technical leadership roles, with experience delivering data, analytics, AI, and cloud-based solutions; 10+ years preferred. Solution Architecture: Experience designing and delivering scalable applications, data and analytics platforms, cloud-native solutions, and integration architectures in an enterprise environment. Advanced Analytics Enablement: Experience partnering with data science teams to design, deploy, and operationalize machine learning and AI solutions in production environments. Technical Expertise: Strong understanding of modern software development practices, cloud and data platforms, CI/CD, security, and operational support. Experience with Python, machine learning concepts, and operationalizing analytical models preferred. Effective communication: Ability to translate complex technical concepts into clear recommendations for business, technical, and senior stakeholder audiences through strong written, verbal, and interpersonal communication. Decision making: Demonstrated ability to evaluate priorities, assess return on investment, resolve obstacles, and make sound architecture recommendations that support business outcomes and enterprise standards. Collaboration and teamwork: Proven ability to influence cross-functional teams, mentor technical staff, build strong stakeholder relationships, and drive successful delivery of strategic initiatives. Leadership mindset: Self-directed, customer-focused professional with strong problem-solving skills and a commitment to delivering high-quality scalable Analytics and AI solutions. Education and Certifications Bachelor's degree in computer science, Information Technology, Data Analytics, Data Science, Engineering, or a related field; equivalent experience considered. Master's degree in information technology, analytics, data science, or related discipline preferred. The hiring range for this position is $121,000 - $198,000 a year. The final salary offer will vary based on geographic location, individual education, skills, and experience. The position is eligible to participate in FM's comprehensive Total Rewards program that includes an incentive plan, medical, dental and vision insurance, life and disability insurance, well-being programs, a 401(k) and pension plan, career development opportunities, tuition reimbursement, flexible work, and time off, including vacation and sick time. FM is an Equal Opportunity Employer and is committed to attracting, developing, and retaining a diverse workforce.
HCA Healthcare is seeking a Senior Data Usability Analyst to join our Data Science & AI team in Healthcare & Medical Services. In this role, you will translate complex clinical and operational data into intuitive, trustworthy, and actionable information products that empower caregivers and leaders. You will partner with data engineers, data scientists, and clinicians to profile data, define business rules, improve data quality, and optimize data models and dashboards for usability and adoption. You will champion data standards, documentation, and governance while mentoring analysts and supporting strategic, patient-centered analytics initiatives. Responsibilities Collaborate with clinicians, operations, and data teams to translate business needs into usable data products Profile and validate clinical and operational data to ensure accuracy, completeness, and consistency Define and maintain business rules, data definitions, and documentation to improve data understanding Design and optimize dashboards, reports, and semantic layers for usability and adoption Identify and drive data quality improvements and standardization across sources and domains Partner with data engineers and data scientists to shape data models and pipelines for analytics use Champion data governance, metadata, and best practices in data usability across the organization Mentor junior analysts and contribute to analytics standards and reusable assets Support strategic analytics and AI initiatives focused on patient-centered care and operational excellence Communicate insights, limitations, and data usability considerations to technical and non-technical stakeholders Required Skills SQLPython or RData visualization (Tableau, Power BI, or similar) Data modeling Data quality and profiling Healthcare data standards (e.g., HL7, FHIR, ICD, CPT) ETL/ELT concepts Statistics and exploratory data analysis Requirements gathering and stakeholder management Data documentation and governance
10/02/2026
Full time
HCA Healthcare is seeking a Senior Data Usability Analyst to join our Data Science & AI team in Healthcare & Medical Services. In this role, you will translate complex clinical and operational data into intuitive, trustworthy, and actionable information products that empower caregivers and leaders. You will partner with data engineers, data scientists, and clinicians to profile data, define business rules, improve data quality, and optimize data models and dashboards for usability and adoption. You will champion data standards, documentation, and governance while mentoring analysts and supporting strategic, patient-centered analytics initiatives. Responsibilities Collaborate with clinicians, operations, and data teams to translate business needs into usable data products Profile and validate clinical and operational data to ensure accuracy, completeness, and consistency Define and maintain business rules, data definitions, and documentation to improve data understanding Design and optimize dashboards, reports, and semantic layers for usability and adoption Identify and drive data quality improvements and standardization across sources and domains Partner with data engineers and data scientists to shape data models and pipelines for analytics use Champion data governance, metadata, and best practices in data usability across the organization Mentor junior analysts and contribute to analytics standards and reusable assets Support strategic analytics and AI initiatives focused on patient-centered care and operational excellence Communicate insights, limitations, and data usability considerations to technical and non-technical stakeholders Required Skills SQLPython or RData visualization (Tableau, Power BI, or similar) Data modeling Data quality and profiling Healthcare data standards (e.g., HL7, FHIR, ICD, CPT) ETL/ELT concepts Statistics and exploratory data analysis Requirements gathering and stakeholder management Data documentation and governance
HCA Healthcare seeks a Senior Data Usability Analyst to join our Data Science & AI team transforming healthcare data into actionable, clinician-friendly insights. You will partner with product, clinical, and engineering teams to assess data quality, standardize definitions, and design intuitive data models, semantic layers, and metrics that improve trust and adoption. Responsibilities include profiling complex healthcare datasets, optimizing data workflows, documenting data standards, and translating user requirements into scalable solutions that support patient-centered care and operational excellence across our hospitals and services. Responsibilities Profile, validate, and monitor data quality across clinical and operational datasets Design and maintain intuitive data models, semantic layers, and standardized metrics Translate clinician and business requirements into scalable data solutions Collaborate with data engineers, data scientists, and product teams to improve data usability Document data definitions, lineage, and usage guidelines for analytics consumers Lead data governance and standardization efforts to ensure consistency and trust Develop dashboards and tools that promote self-service analytics adoption Conduct user research and feedback sessions to refine data products Support AI and advanced analytics initiatives with well-structured, reliable data Mentor junior analysts on data usability best practices and healthcare data standards Required Skills SQLData modeling and dimensional modeling Data quality assessment and profiling Healthcare data standards (ICD, CPT, HL7, FHIR, etc.) Data visualization (Tableau, Power BI, or similar) Metadata management and data cataloging Requirements gathering and stakeholder management ETL/ELT and data pipeline concepts Cloud data platforms (AWS, Azure, or GCP) Statistical analysis and exploratory data analysis
10/02/2026
Full time
HCA Healthcare seeks a Senior Data Usability Analyst to join our Data Science & AI team transforming healthcare data into actionable, clinician-friendly insights. You will partner with product, clinical, and engineering teams to assess data quality, standardize definitions, and design intuitive data models, semantic layers, and metrics that improve trust and adoption. Responsibilities include profiling complex healthcare datasets, optimizing data workflows, documenting data standards, and translating user requirements into scalable solutions that support patient-centered care and operational excellence across our hospitals and services. Responsibilities Profile, validate, and monitor data quality across clinical and operational datasets Design and maintain intuitive data models, semantic layers, and standardized metrics Translate clinician and business requirements into scalable data solutions Collaborate with data engineers, data scientists, and product teams to improve data usability Document data definitions, lineage, and usage guidelines for analytics consumers Lead data governance and standardization efforts to ensure consistency and trust Develop dashboards and tools that promote self-service analytics adoption Conduct user research and feedback sessions to refine data products Support AI and advanced analytics initiatives with well-structured, reliable data Mentor junior analysts on data usability best practices and healthcare data standards Required Skills SQLData modeling and dimensional modeling Data quality assessment and profiling Healthcare data standards (ICD, CPT, HL7, FHIR, etc.) Data visualization (Tableau, Power BI, or similar) Metadata management and data cataloging Requirements gathering and stakeholder management ETL/ELT and data pipeline concepts Cloud data platforms (AWS, Azure, or GCP) Statistical analysis and exploratory data analysis
HCA Healthcare is seeking a Senior Data Usability Analyst to join our Data Science & AI team in the Healthcare & Medical Services industry. In this role, you will translate complex clinical and operational data into intuitive, high-quality data assets that are easy for clinicians, leaders, and analysts to discover, trust, and use. You will define data usability standards, drive metadata and data catalog initiatives, profile and validate large datasets, and partner with engineers and data scientists to optimize data models. You will collaborate with stakeholders to understand workflows, improve data quality, and ensure data solutions support patient-centered care and strategic decisions. Responsibilities Define and enforce data usability and quality standards across clinical and operational domains Profile, validate, and document large healthcare datasets for accuracy, completeness, and accessibility Partner with data engineers and data scientists to design and refine data models and pipelines Lead metadata, data catalog, and documentation efforts to improve data discoverability Collaborate with clinicians and business stakeholders to understand workflows and translate needs into usable data assets Develop and maintain KPIs and metrics to monitor data usability and adoption Support governance processes and ensure data solutions align with regulatory and privacy requirements Provide guidance and mentorship on best practices for data usability and documentation Required Skills SQLData modeling Data profiling and quality assessment Metadata management and data catalog tools ETL/ELT and data pipeline concepts Python or R for data analysis Healthcare data standards (e.g., HL7, FHIR, claims/EMR data) BI/visualization tools (e.g., Tableau, Power BI, Looker) Requirements gathering and stakeholder communication Data governance and documentation
10/02/2026
Full time
HCA Healthcare is seeking a Senior Data Usability Analyst to join our Data Science & AI team in the Healthcare & Medical Services industry. In this role, you will translate complex clinical and operational data into intuitive, high-quality data assets that are easy for clinicians, leaders, and analysts to discover, trust, and use. You will define data usability standards, drive metadata and data catalog initiatives, profile and validate large datasets, and partner with engineers and data scientists to optimize data models. You will collaborate with stakeholders to understand workflows, improve data quality, and ensure data solutions support patient-centered care and strategic decisions. Responsibilities Define and enforce data usability and quality standards across clinical and operational domains Profile, validate, and document large healthcare datasets for accuracy, completeness, and accessibility Partner with data engineers and data scientists to design and refine data models and pipelines Lead metadata, data catalog, and documentation efforts to improve data discoverability Collaborate with clinicians and business stakeholders to understand workflows and translate needs into usable data assets Develop and maintain KPIs and metrics to monitor data usability and adoption Support governance processes and ensure data solutions align with regulatory and privacy requirements Provide guidance and mentorship on best practices for data usability and documentation Required Skills SQLData modeling Data profiling and quality assessment Metadata management and data catalog tools ETL/ELT and data pipeline concepts Python or R for data analysis Healthcare data standards (e.g., HL7, FHIR, claims/EMR data) BI/visualization tools (e.g., Tableau, Power BI, Looker) Requirements gathering and stakeholder communication Data governance and documentation
Job Description Job Description About Medical Guardian: Medical Guardian is a fast-growing digital health and safety company on a mission to help people live a life without limits. With 13 consecutive years on the Inc. 5000 list of Fastest Growing Companies, we are redefining what it means to age confidently and independently. We support over 625,000 members nationwide with life-saving emergency response systems and remote patient monitoring solutions. Trusted by families, healthcare providers, and care managers, our work is powered by a culture of innovation, compassion, and purpose. Mission: This role is focused on building and leading the data engineering foundation that powers real-time decisioning, operational applications, analytics, ML/AI model development, and data services across Medical Guardian. The Principal Data Engineer will own the design, delivery, and maturity of production-grade data pipelines and data platforms, with a primary emphasis on real-time streaming, IoT telemetry, Databricks, Azure, data services for APIs and microservices, and reliable data products for downstream consumption. Role Summary: We are looking for a Principal Data Engineer to serve as a hands-on technical and people leader for data engineering, data platform architecture, real-time streaming, and production data services. This role will focus on designing, building, operating, and improving data pipelines and data products while also bringing principal-level judgment to architecture, stakeholder shaping, delivery priorities, team management, and production readiness. This is a hands-on engineering leadership role first. The ideal candidate should be comfortable spending significant time working directly with Databricks, Spark, SQL, Python/PySpark, Azure services, streaming architectures, data quality frameworks, pipeline automation, CI/CD, and production troubleshooting. They should also be able to operate with the maturity of a principal-level leader: shaping unclear requirements, making pragmatic technical decisions, managing and mentoring engineers, and driving work forward without waiting for perfect specifications. This is a fast-moving, startup-like environment. Requirements may be incomplete, priorities may evolve, and the right candidate will help create clarity while building quickly. We need someone who can move from ambiguous business need to reliable data capability with urgency, discipline, and ownership. Stakeholder shaping is a critical part of this role. The Principal Data Engineer should be able to work directly with business, product, software engineering, analytics, ML/AI, operations, and leadership stakeholders to define what data needs to exist, how it should be consumed, what production guarantees are required, and how success should be measured. A background in commercial software, SaaS, digital products, healthtech, fintech, IoT, data platforms, or other product-driven environments is strongly preferred. We want someone who understands that data pipelines and data services are not just technical artifacts. They are product capabilities that support real users, real workflows, operational decisions, ML/AI systems, APIs, analytics, and measurable business outcomes. Key Responsibilities: Hands-On Data Engineering and Platform Development Design, build, optimize, and operate production-grade batch and streaming data pipelines on Azure and Databricks, with a primary focus on real-time IoT and telemetry use cases within a Medallion architecture. Develop ETL/ELT workflows to ingest, transform, validate, and serve large volumes of structured, semi-structured, unstructured, and streaming data. Build and maintain reliable data products, data services, APIs, and microservices that support operational applications, analytics, software engineering, and ML/AI teams. Use Python, PySpark, Spark SQL, SQL, Delta Lake, Databricks Workflows, CI/CD, and related tools to build maintainable, testable, and observable data systems. Troubleshoot complex production pipeline issues across Databricks, Azure, streaming systems, APIs, and source systems, including root cause analysis, corrective action, and prevention planning. Move quickly from rough business need to prototype, pilot, and production-ready data capability while maintaining appropriate engineering discipline. Real-Time Streaming, IoT Telemetry, and Operational Data Services Lead the design and delivery of real-time streaming ingestion and processing patterns for connected medical device telemetry, event data, and operational data feeds. Implement streaming solutions using Azure Event Hubs, Azure Stream Analytics, Databricks, Delta Lake, and related Azure integration patterns. Design cost-effective throughput, partitioning, delivery, retention, and replay strategies for high-volume event and telemetry workloads. Create consumption patterns that support APIs, microservices, operational applications, near-real-time decisioning, analytics, and ML/AI use cases. Define reliability, latency, quality, observability, and supportability expectations for production streaming systems. Databricks, Lakehouse, and Data Platform Architecture Set direction for Databricks-based data engineering patterns, including Medallion architecture, Delta Lake, Spark optimization, data modeling, data quality, and reusable pipeline design. Optimize production Databricks pipelines using PySpark, Spark SQL, Delta Lake, partitioning strategies, caching, shuffle optimization, cluster/job configuration, and cost-aware design. Establish practical standards for pipeline structure, code organization, testing, deployment, monitoring, documentation, and ownership. Partner with data platform, security, infrastructure, and engineering teams to ensure the data platform is scalable, secure, reliable, and aligned with enterprise architecture. Make pragmatic architecture tradeoffs between speed, durability, cost, governance, performance, and downstream business impact. Stakeholder Shaping and Cross-Functional Partnership Work directly with business, product, analytics, ML/AI, operations, software engineering, and leadership stakeholders to clarify what data is needed, why it matters, how it will be used, and what success looks like. Translate ambiguous business needs into concrete data requirements, data product definitions, architecture options, delivery priorities, and implementation plans. Ask practical questions early: who will use the data, what decision or workflow does it support, what latency and quality are required, what happens if the data is wrong or late, and how will we know the capability is creating value? Help the organization avoid becoming a data ticket factory by shaping solutions, not just executing requests. Communicate architecture decisions, tradeoffs, risks, dependencies, and delivery options clearly to technical and non-technical stakeholders. Team Management and Principal-Level Technical Leadership Manage, mentor, and develop data engineers, providing clear expectations, technical guidance, prioritization support, feedback, and accountability. Provide technical leadership through hands-on example, strong engineering judgment, clear recommendations, and pragmatic decision-making. Lead design reviews, code reviews, production readiness reviews, incident reviews, and architecture discussions across data engineering initiatives. Establish and improve engineering standards for data quality, testing, CI/CD, observability, documentation, runbooks, cost management, privacy, and security. Proactively identify platform risks, data gaps, unclear ownership, operational weaknesses, and opportunities to improve reliability, scalability, and delivery speed. Influence without relying only on formal authority by building trust, framing tradeoffs, and helping cross-functional teams get to decisions. ML/AI, Analytics, and GenAI Enablement Partner with ML engineers, data scientists, analytics engineers, and analysts to deliver reliable data pipelines, feature pipelines, training datasets, scoring inputs, and feedback loops. Support the data foundation for predictive models, risk scores, operational decisioning, GenAI workflows, RAG, document intelligence, summarization, and AI-enabled automation. Help define data contracts, model-ready datasets, feature definitions, lineage, and monitoring expectations for ML/AI and analytics use cases. Ensure downstream consumers understand the meaning, freshness, quality, limitations, and appropriate use of the data products they depend on. Governance, Data Quality, Security, and Production Operations Apply privacy-first, security-aware, and governance-aligned practices for regulated, sensitive, and operationally critical data. Design and implement data quality checks, validation rules, anomaly detection, schema expectations, alerting, and operational monitoring. Ensure production pipelines and services are supportable, observable, documented, recoverable, and aligned with business continuity needs. Drive incident response and continuous improvement for data platform and pipeline issues, including root cause analysis and preventative remediation. Balance innovation with reliability, compliance, privacy, cost discipline, and operational usefulness. Required Qualifications: 10+ years of professional experience in data engineering . click apply for full job details
09/29/2026
Full time
Job Description Job Description About Medical Guardian: Medical Guardian is a fast-growing digital health and safety company on a mission to help people live a life without limits. With 13 consecutive years on the Inc. 5000 list of Fastest Growing Companies, we are redefining what it means to age confidently and independently. We support over 625,000 members nationwide with life-saving emergency response systems and remote patient monitoring solutions. Trusted by families, healthcare providers, and care managers, our work is powered by a culture of innovation, compassion, and purpose. Mission: This role is focused on building and leading the data engineering foundation that powers real-time decisioning, operational applications, analytics, ML/AI model development, and data services across Medical Guardian. The Principal Data Engineer will own the design, delivery, and maturity of production-grade data pipelines and data platforms, with a primary emphasis on real-time streaming, IoT telemetry, Databricks, Azure, data services for APIs and microservices, and reliable data products for downstream consumption. Role Summary: We are looking for a Principal Data Engineer to serve as a hands-on technical and people leader for data engineering, data platform architecture, real-time streaming, and production data services. This role will focus on designing, building, operating, and improving data pipelines and data products while also bringing principal-level judgment to architecture, stakeholder shaping, delivery priorities, team management, and production readiness. This is a hands-on engineering leadership role first. The ideal candidate should be comfortable spending significant time working directly with Databricks, Spark, SQL, Python/PySpark, Azure services, streaming architectures, data quality frameworks, pipeline automation, CI/CD, and production troubleshooting. They should also be able to operate with the maturity of a principal-level leader: shaping unclear requirements, making pragmatic technical decisions, managing and mentoring engineers, and driving work forward without waiting for perfect specifications. This is a fast-moving, startup-like environment. Requirements may be incomplete, priorities may evolve, and the right candidate will help create clarity while building quickly. We need someone who can move from ambiguous business need to reliable data capability with urgency, discipline, and ownership. Stakeholder shaping is a critical part of this role. The Principal Data Engineer should be able to work directly with business, product, software engineering, analytics, ML/AI, operations, and leadership stakeholders to define what data needs to exist, how it should be consumed, what production guarantees are required, and how success should be measured. A background in commercial software, SaaS, digital products, healthtech, fintech, IoT, data platforms, or other product-driven environments is strongly preferred. We want someone who understands that data pipelines and data services are not just technical artifacts. They are product capabilities that support real users, real workflows, operational decisions, ML/AI systems, APIs, analytics, and measurable business outcomes. Key Responsibilities: Hands-On Data Engineering and Platform Development Design, build, optimize, and operate production-grade batch and streaming data pipelines on Azure and Databricks, with a primary focus on real-time IoT and telemetry use cases within a Medallion architecture. Develop ETL/ELT workflows to ingest, transform, validate, and serve large volumes of structured, semi-structured, unstructured, and streaming data. Build and maintain reliable data products, data services, APIs, and microservices that support operational applications, analytics, software engineering, and ML/AI teams. Use Python, PySpark, Spark SQL, SQL, Delta Lake, Databricks Workflows, CI/CD, and related tools to build maintainable, testable, and observable data systems. Troubleshoot complex production pipeline issues across Databricks, Azure, streaming systems, APIs, and source systems, including root cause analysis, corrective action, and prevention planning. Move quickly from rough business need to prototype, pilot, and production-ready data capability while maintaining appropriate engineering discipline. Real-Time Streaming, IoT Telemetry, and Operational Data Services Lead the design and delivery of real-time streaming ingestion and processing patterns for connected medical device telemetry, event data, and operational data feeds. Implement streaming solutions using Azure Event Hubs, Azure Stream Analytics, Databricks, Delta Lake, and related Azure integration patterns. Design cost-effective throughput, partitioning, delivery, retention, and replay strategies for high-volume event and telemetry workloads. Create consumption patterns that support APIs, microservices, operational applications, near-real-time decisioning, analytics, and ML/AI use cases. Define reliability, latency, quality, observability, and supportability expectations for production streaming systems. Databricks, Lakehouse, and Data Platform Architecture Set direction for Databricks-based data engineering patterns, including Medallion architecture, Delta Lake, Spark optimization, data modeling, data quality, and reusable pipeline design. Optimize production Databricks pipelines using PySpark, Spark SQL, Delta Lake, partitioning strategies, caching, shuffle optimization, cluster/job configuration, and cost-aware design. Establish practical standards for pipeline structure, code organization, testing, deployment, monitoring, documentation, and ownership. Partner with data platform, security, infrastructure, and engineering teams to ensure the data platform is scalable, secure, reliable, and aligned with enterprise architecture. Make pragmatic architecture tradeoffs between speed, durability, cost, governance, performance, and downstream business impact. Stakeholder Shaping and Cross-Functional Partnership Work directly with business, product, analytics, ML/AI, operations, software engineering, and leadership stakeholders to clarify what data is needed, why it matters, how it will be used, and what success looks like. Translate ambiguous business needs into concrete data requirements, data product definitions, architecture options, delivery priorities, and implementation plans. Ask practical questions early: who will use the data, what decision or workflow does it support, what latency and quality are required, what happens if the data is wrong or late, and how will we know the capability is creating value? Help the organization avoid becoming a data ticket factory by shaping solutions, not just executing requests. Communicate architecture decisions, tradeoffs, risks, dependencies, and delivery options clearly to technical and non-technical stakeholders. Team Management and Principal-Level Technical Leadership Manage, mentor, and develop data engineers, providing clear expectations, technical guidance, prioritization support, feedback, and accountability. Provide technical leadership through hands-on example, strong engineering judgment, clear recommendations, and pragmatic decision-making. Lead design reviews, code reviews, production readiness reviews, incident reviews, and architecture discussions across data engineering initiatives. Establish and improve engineering standards for data quality, testing, CI/CD, observability, documentation, runbooks, cost management, privacy, and security. Proactively identify platform risks, data gaps, unclear ownership, operational weaknesses, and opportunities to improve reliability, scalability, and delivery speed. Influence without relying only on formal authority by building trust, framing tradeoffs, and helping cross-functional teams get to decisions. ML/AI, Analytics, and GenAI Enablement Partner with ML engineers, data scientists, analytics engineers, and analysts to deliver reliable data pipelines, feature pipelines, training datasets, scoring inputs, and feedback loops. Support the data foundation for predictive models, risk scores, operational decisioning, GenAI workflows, RAG, document intelligence, summarization, and AI-enabled automation. Help define data contracts, model-ready datasets, feature definitions, lineage, and monitoring expectations for ML/AI and analytics use cases. Ensure downstream consumers understand the meaning, freshness, quality, limitations, and appropriate use of the data products they depend on. Governance, Data Quality, Security, and Production Operations Apply privacy-first, security-aware, and governance-aligned practices for regulated, sensitive, and operationally critical data. Design and implement data quality checks, validation rules, anomaly detection, schema expectations, alerting, and operational monitoring. Ensure production pipelines and services are supportable, observable, documented, recoverable, and aligned with business continuity needs. Drive incident response and continuous improvement for data platform and pipeline issues, including root cause analysis and preventative remediation. Balance innovation with reliability, compliance, privacy, cost discipline, and operational usefulness. Required Qualifications: 10+ years of professional experience in data engineering . click apply for full job details
Job Description Job Description Our mission is to create the Experience of a Lifetime for our employees, so they can, in turn, create the Experience of a Lifetime for our guests. We own and operate the most renowned destination resorts in the world as well as regional and local ski areas outside major cities, and connect them all through one unrivaled network. We are looking for ambitious leaders, innovators and creators to join our talented team. If you're ready to pursue your fullest potential, we want to get to know you! Candidates for year-round positions are reviewed on a rolling basis. Applications will be accepted up to 90 days after the posting date, or until the position is filled (whichever is first). Job Summary: We are looking for a curious, driven, innovative machine learning engineer who takes initiative to solve problems and create environments that accelerate the development, deployment, and usage of data science models and AI to drive greater organizational impact. The Data Science & Data Engineering team within the Enterprise Analytics organization builds data assets, predictive models, analytical applications, and platforms across the organization. Our team collaborates with business stakeholders, analysts, and technology teams to tackle high-impact use cases with state-of-the-art models and tools to grow the business, streamline costs, and improve guest experiences. Job Specifications: Starting Wage: $140,000 - $185,000 + Annual Bonus Employment Type: Year Round Shift Type: Full Time hours Minimum Age: At least 18 years of age Housing Availability: No Job Responsibilities: Productionize ML models developed by data science into reliable, monitored, maintainable systems. Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable. Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows. Identify and scope opportunities for ML engineering across the business for high-impact. Develop reusable tools , libraries, standards, documentation, and production-readiness practices to enable data science and data engineering teams. Develop analytical and model-powered applications that turn data and ML outputs into usable business workflows for end users. Prepare the platform for future AI engineering , including LLM and agent-based systems, as the organization matures. Provide technical leadership and mentoring across engineering, architecture, and development including design and code reviews. Job Requirements: Technical Skills: Quantitative Foundation : B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering). Software Engineering Fundamentals: write clean, modular, testable, maintainable code and understand how to structure production-grade systems rather than one-off notebooks or scripts. Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services. Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage. ML Lifecycle Fluency: understand the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement. Production ML Patterns: understand core MLOps patterns such as model registries, feature/data versioning, reproducible environments, testing/validation, monitoring, and rollback. Cloud and Platform Engineering: You are comfortable working in cloud-based data and ML environments and understand the foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture. Databricks Expertise : You're familiar and experienced with the core parts of Spark, Unity Catalog, Delta Lake, Databricks Workflows, MLflow, model registry patterns, job/cluster optimization, and governance. DevOps Practices: You use modern engineering practices such as Git, CI/CD, automated testing, code review, dependency management, environment management, and observability. Application Development : You can build applications, APIs, dashboards, or workflow tools that sit on top of data and model outputs. System Design: You can reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use. Soft Skills: Curious : bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning. Ownership : take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions. Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences. Collaboration: work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders. Pragmatism : You know how to balance ideal architecture with business urgency, team maturity, operational constraints, and the need to ship. Preferred qualifications: A graduate degree (Masters or PhD) in a quantitative field Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management Experience with AI engineer to use, build, and monitor agentic solutions The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors. Job Benefits Ski/Mountain Perks! Free passes for employees, employee discounted lift tickets for friends and family AND free ski lessons MORE employee discounts on lodging, food, gear, and mountain shuttles 401(k) Retirement Plan Employee Assistance Program Excellent training and professional development Full Time roles are eligible for the above, plus: Health Insurance; Medical Insurance, Dental Insurance, and Vision Insurance plans (for eligible seasonal employees after working 500 hours) Free ski passes for dependents Critical Illness and Accident plans Employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states in which we currently operate. This includes: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, and Wyoming. Please note that the ability to work in person or off-site, and the particulars related to such work, are subject to change at any time; and, accordingly, the Company reserves the right to change its policies and/or require in-person/in-office work or off-site work at any time in its sole discretion. In completing this application, and when submitting related documentation, applicants may redact information that identifies their age, date of birth, and/or dates of attendance at or graduation from an educational institution. We follow all federal, state, and local laws including restrictions on child/minor labor. Minors hired into this position will not be asked or permitted to engage in any activities restricted to adult workers. Vail Resorts is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status or any other status protected by applicable law. Requisition ID 517322 Reference Date: 09/05/2026 Job Code Function: Data Science
09/28/2026
Full time
Job Description Job Description Our mission is to create the Experience of a Lifetime for our employees, so they can, in turn, create the Experience of a Lifetime for our guests. We own and operate the most renowned destination resorts in the world as well as regional and local ski areas outside major cities, and connect them all through one unrivaled network. We are looking for ambitious leaders, innovators and creators to join our talented team. If you're ready to pursue your fullest potential, we want to get to know you! Candidates for year-round positions are reviewed on a rolling basis. Applications will be accepted up to 90 days after the posting date, or until the position is filled (whichever is first). Job Summary: We are looking for a curious, driven, innovative machine learning engineer who takes initiative to solve problems and create environments that accelerate the development, deployment, and usage of data science models and AI to drive greater organizational impact. The Data Science & Data Engineering team within the Enterprise Analytics organization builds data assets, predictive models, analytical applications, and platforms across the organization. Our team collaborates with business stakeholders, analysts, and technology teams to tackle high-impact use cases with state-of-the-art models and tools to grow the business, streamline costs, and improve guest experiences. Job Specifications: Starting Wage: $140,000 - $185,000 + Annual Bonus Employment Type: Year Round Shift Type: Full Time hours Minimum Age: At least 18 years of age Housing Availability: No Job Responsibilities: Productionize ML models developed by data science into reliable, monitored, maintainable systems. Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable. Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows. Identify and scope opportunities for ML engineering across the business for high-impact. Develop reusable tools , libraries, standards, documentation, and production-readiness practices to enable data science and data engineering teams. Develop analytical and model-powered applications that turn data and ML outputs into usable business workflows for end users. Prepare the platform for future AI engineering , including LLM and agent-based systems, as the organization matures. Provide technical leadership and mentoring across engineering, architecture, and development including design and code reviews. Job Requirements: Technical Skills: Quantitative Foundation : B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering). Software Engineering Fundamentals: write clean, modular, testable, maintainable code and understand how to structure production-grade systems rather than one-off notebooks or scripts. Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services. Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage. ML Lifecycle Fluency: understand the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement. Production ML Patterns: understand core MLOps patterns such as model registries, feature/data versioning, reproducible environments, testing/validation, monitoring, and rollback. Cloud and Platform Engineering: You are comfortable working in cloud-based data and ML environments and understand the foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture. Databricks Expertise : You're familiar and experienced with the core parts of Spark, Unity Catalog, Delta Lake, Databricks Workflows, MLflow, model registry patterns, job/cluster optimization, and governance. DevOps Practices: You use modern engineering practices such as Git, CI/CD, automated testing, code review, dependency management, environment management, and observability. Application Development : You can build applications, APIs, dashboards, or workflow tools that sit on top of data and model outputs. System Design: You can reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use. Soft Skills: Curious : bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning. Ownership : take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions. Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences. Collaboration: work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders. Pragmatism : You know how to balance ideal architecture with business urgency, team maturity, operational constraints, and the need to ship. Preferred qualifications: A graduate degree (Masters or PhD) in a quantitative field Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management Experience with AI engineer to use, build, and monitor agentic solutions The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors. Job Benefits Ski/Mountain Perks! Free passes for employees, employee discounted lift tickets for friends and family AND free ski lessons MORE employee discounts on lodging, food, gear, and mountain shuttles 401(k) Retirement Plan Employee Assistance Program Excellent training and professional development Full Time roles are eligible for the above, plus: Health Insurance; Medical Insurance, Dental Insurance, and Vision Insurance plans (for eligible seasonal employees after working 500 hours) Free ski passes for dependents Critical Illness and Accident plans Employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states in which we currently operate. This includes: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, and Wyoming. Please note that the ability to work in person or off-site, and the particulars related to such work, are subject to change at any time; and, accordingly, the Company reserves the right to change its policies and/or require in-person/in-office work or off-site work at any time in its sole discretion. In completing this application, and when submitting related documentation, applicants may redact information that identifies their age, date of birth, and/or dates of attendance at or graduation from an educational institution. We follow all federal, state, and local laws including restrictions on child/minor labor. Minors hired into this position will not be asked or permitted to engage in any activities restricted to adult workers. Vail Resorts is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status or any other status protected by applicable law. Requisition ID 517322 Reference Date: 09/05/2026 Job Code Function: Data Science
Job Description Job Description H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in Dallas, Texas and requires onsite customer interfacing. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.
09/28/2026
Full time
Job Description Job Description H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in Dallas, Texas and requires onsite customer interfacing. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.
Job Description Job Description Staff / Principal Platform Engineer Location: New York City Hybrid Department: AI Platform & Infrastructure Team Reports to: Vangie Shue - Principal Engineering Manager About AppGate AppGate secures and protects an organization's most valuable assets with its high performance Zero Trust Network Access (ZTNA) solution and Cyber Advisory Services. AppGate ZTNA is the only direct-routed Zero Trust solution built for peak performance, superior protection and seamless interoperability. AppGate Cyber Advisory Services harden your security posture and ensure business continuity. AppGate safeguards Fortune 500 enterprises and government agencies worldwide. Learn more at About the Role As we expand our platform, we are standing up a new AI Platform & Infrastructure team: the engine room of AppGate's AI strategy. This team owns the infrastructure layer that every next-generation security capability is built on, from network observability to AI-driven threat detection and the secure operation of emerging Agentic AI systems. We're looking for a Staff or Principal Platform Engineer to build and operate the foundational platform behind AppGate's AI products. You combine deep DevOps and cloud infrastructure expertise with hands-on experience operationalizing AI/ML systems, and you treat observability as a first-class engineering discipline. This is a rare opportunity to join a small, private, high-impact company where your work directly shapes the architecture, reliability and core platform that defines the future of security. You'll own the platform spanning APIs, cloud and self-managed solutions and AI/ML infrastructure, and you'll make it fast, reliable and observable at scale. This is a high-leverage, hands-on role for a senior engineer who sets technical direction and still ships. Key Responsibilities Build the Platform: design, build and operate the cloud infrastructure, services and pipelines that AppGate's AI and cloud products run on. Strong experience with self-managed technologies (kafka, elasticsearch) and Kubernetes are a must. Infrastructure as Code & Deployment Orchestration: Terraform and Helm for cloud provisioning, service deployment and configuration management. Implement Observability: instrument APIs, cloud services and AI/ML infrastructure with metrics, logging, tracing and alerting, and define SLOs and operational health metrics that teams trust. Data Platform: real-time and batch data ingestion pipelines, feature stores and data quality. Integrations: third-party connectors, APIs and platform integrations. Operationalize AI/ML: build model serving and inference pipelines, experiment tracking and the MLOps tooling for deployment, versioning, drift monitoring and lifecycle management. Engineer for reliability & automation: apply SRE practices to reduce toil, improve resilience and keep latency and uptime within target across the platform. Automate everything - deliver infrastructure-as-code, CI/CD and self-service tooling so product teams ship safely and quickly. Set technical direction: define platform standards, architecture and best practices, and raise the engineering bar through design reviews and mentorship. Collaborate cross-functionally: partner with data scientists, product teams and leadership to align platform investment with AppGate's strategic vision. Required Qualifications Experience: extensive platform, infrastructure or SRE engineering experience, with a track record of operating production systems at scale. Staff-level candidates typically bring 8+ years and Principal-level candidates 12+ years, though we hire on demonstrated impact. DevOps depth: strong command of infrastructure-as-code (Terraform or equivalent), CI/CD, containers and orchestration (Docker, Kubernetes), and cloud platforms (AWS). Observability expertise: hands-on experience implementing observability across APIs, cloud services and distributed systems using tools such as Prometheus, Grafana, OpenTelemetry, the ELK stack or comparable, including SLO and error-budget practice. Data platform skills: familiarity with real-time and batch ingestion pipelines, feature stores and data quality at production scale. Engineering craft: fluency in a primary backend language (Python, Go or similar) and a strong bias toward automation, testing and reliable, maintainable systems. Leadership: a record of setting technical direction, leading complex initiatives across teams, mentoring senior engineers, while still being very hands-on. Mindset: pragmatic, rigorous and ownership-driven. You thrive in a small, fast-moving environment and enjoy building foundations others depend on. Preferred Qualifications AI/ML infrastructure: experience building or operating model serving, inference pipelines and MLOps tooling such as MLflow, Kubeflow, SageMaker or equivalent, including model deployment, versioning and drift monitoring. Networking & Zero Trust fundamentals: working knowledge of the network and routing layer beneath modern access solutions - TCP/IP, TLS, tunneling/overlay networks, packet routing and filtering, DNS and firewalling - and familiarity with Zero Trust Network Access (ZTNA) or adjacent domains (VPN, SDP, SASE, software-defined networking). You can reason about traffic paths, latency and throughput end-to-end, and instrument the network as a first-class observability signal. Compensation Staff: 185k-225k base Principal: 215k-270k base We offer performance bonuses and considerable equity. AppGate is An Equal Opportunity/Affirmative Action Employer and a federal contractor subject to the Rehabilitation Act of 1973 and the Vietnam Era Veterans Readjustment Assistance Act of 1974 as amended, and their corresponding regulations. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class. Further, AppGate is an affirmative action employer committed to taking positive steps to employ, advance in employment and otherwise afford equal employment opportunity to protected veterans and individuals with disabilities. In furtherance of AppGate's policy regarding affirmative action and equal employment opportunity, AppGate has developed a written affirmative action program. This program is available for review upon request by any applicant or employee during normal business hours by contacting the company's EEO Coordinator.
09/28/2026
Full time
Job Description Job Description Staff / Principal Platform Engineer Location: New York City Hybrid Department: AI Platform & Infrastructure Team Reports to: Vangie Shue - Principal Engineering Manager About AppGate AppGate secures and protects an organization's most valuable assets with its high performance Zero Trust Network Access (ZTNA) solution and Cyber Advisory Services. AppGate ZTNA is the only direct-routed Zero Trust solution built for peak performance, superior protection and seamless interoperability. AppGate Cyber Advisory Services harden your security posture and ensure business continuity. AppGate safeguards Fortune 500 enterprises and government agencies worldwide. Learn more at About the Role As we expand our platform, we are standing up a new AI Platform & Infrastructure team: the engine room of AppGate's AI strategy. This team owns the infrastructure layer that every next-generation security capability is built on, from network observability to AI-driven threat detection and the secure operation of emerging Agentic AI systems. We're looking for a Staff or Principal Platform Engineer to build and operate the foundational platform behind AppGate's AI products. You combine deep DevOps and cloud infrastructure expertise with hands-on experience operationalizing AI/ML systems, and you treat observability as a first-class engineering discipline. This is a rare opportunity to join a small, private, high-impact company where your work directly shapes the architecture, reliability and core platform that defines the future of security. You'll own the platform spanning APIs, cloud and self-managed solutions and AI/ML infrastructure, and you'll make it fast, reliable and observable at scale. This is a high-leverage, hands-on role for a senior engineer who sets technical direction and still ships. Key Responsibilities Build the Platform: design, build and operate the cloud infrastructure, services and pipelines that AppGate's AI and cloud products run on. Strong experience with self-managed technologies (kafka, elasticsearch) and Kubernetes are a must. Infrastructure as Code & Deployment Orchestration: Terraform and Helm for cloud provisioning, service deployment and configuration management. Implement Observability: instrument APIs, cloud services and AI/ML infrastructure with metrics, logging, tracing and alerting, and define SLOs and operational health metrics that teams trust. Data Platform: real-time and batch data ingestion pipelines, feature stores and data quality. Integrations: third-party connectors, APIs and platform integrations. Operationalize AI/ML: build model serving and inference pipelines, experiment tracking and the MLOps tooling for deployment, versioning, drift monitoring and lifecycle management. Engineer for reliability & automation: apply SRE practices to reduce toil, improve resilience and keep latency and uptime within target across the platform. Automate everything - deliver infrastructure-as-code, CI/CD and self-service tooling so product teams ship safely and quickly. Set technical direction: define platform standards, architecture and best practices, and raise the engineering bar through design reviews and mentorship. Collaborate cross-functionally: partner with data scientists, product teams and leadership to align platform investment with AppGate's strategic vision. Required Qualifications Experience: extensive platform, infrastructure or SRE engineering experience, with a track record of operating production systems at scale. Staff-level candidates typically bring 8+ years and Principal-level candidates 12+ years, though we hire on demonstrated impact. DevOps depth: strong command of infrastructure-as-code (Terraform or equivalent), CI/CD, containers and orchestration (Docker, Kubernetes), and cloud platforms (AWS). Observability expertise: hands-on experience implementing observability across APIs, cloud services and distributed systems using tools such as Prometheus, Grafana, OpenTelemetry, the ELK stack or comparable, including SLO and error-budget practice. Data platform skills: familiarity with real-time and batch ingestion pipelines, feature stores and data quality at production scale. Engineering craft: fluency in a primary backend language (Python, Go or similar) and a strong bias toward automation, testing and reliable, maintainable systems. Leadership: a record of setting technical direction, leading complex initiatives across teams, mentoring senior engineers, while still being very hands-on. Mindset: pragmatic, rigorous and ownership-driven. You thrive in a small, fast-moving environment and enjoy building foundations others depend on. Preferred Qualifications AI/ML infrastructure: experience building or operating model serving, inference pipelines and MLOps tooling such as MLflow, Kubeflow, SageMaker or equivalent, including model deployment, versioning and drift monitoring. Networking & Zero Trust fundamentals: working knowledge of the network and routing layer beneath modern access solutions - TCP/IP, TLS, tunneling/overlay networks, packet routing and filtering, DNS and firewalling - and familiarity with Zero Trust Network Access (ZTNA) or adjacent domains (VPN, SDP, SASE, software-defined networking). You can reason about traffic paths, latency and throughput end-to-end, and instrument the network as a first-class observability signal. Compensation Staff: 185k-225k base Principal: 215k-270k base We offer performance bonuses and considerable equity. AppGate is An Equal Opportunity/Affirmative Action Employer and a federal contractor subject to the Rehabilitation Act of 1973 and the Vietnam Era Veterans Readjustment Assistance Act of 1974 as amended, and their corresponding regulations. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class. Further, AppGate is an affirmative action employer committed to taking positive steps to employ, advance in employment and otherwise afford equal employment opportunity to protected veterans and individuals with disabilities. In furtherance of AppGate's policy regarding affirmative action and equal employment opportunity, AppGate has developed a written affirmative action program. This program is available for review upon request by any applicant or employee during normal business hours by contacting the company's EEO Coordinator.
Job Description Job Description Job Description Technical Team Lead - Business Intelligence Platform Columbia, MD Full Time TS/SCI with Polygraph Required Position: Technical Team Lead (Software Engineer, Level 3) Location: Columbia, MD (on-site) Category: Software Engineering / Technical Leadership / Data Engineering Clearance Requirement: Active TS/SCI with Polygraph Compensation: $200,000 - $250,000 (annualized USD) Experience Requirement: 12+ years with a Bachelor's degree, OR 10+ years with a Master's degree, OR 4 additional years of relevant experience in lieu of a degree Description Serve as the Technical Team Lead for the Mission Intelligence (MI) team, supporting data engineering, analytics, and automation initiatives. The MI team operates a business intelligence platform that enables enterprise-wide, data-driven decision-making. Your primary responsibility is to ensure the reliability, availability, and quality of this high-impact platform. This is a leadership-leaning role with real engineering teeth: you'll mentor engineers, unblock execution, set technical direction, and quietly hold the line on quality across the platform. Responsibilities Gather stakeholder requirements, assess available data, and develop solutions for delivering key metrics. Break down complex work into actionable steps that demonstrate consistent progress. Remove technical obstacles, manage expectations, and support team execution. Define and communicate task scope through clear documentation and tracking systems. Enable the team to integrate Site Reliability Engineering practices into the operational platform. Mentor and guide junior software engineers and data scientists. Produce project management materials such as agendas, meeting notes, and design decision records. Skills Requirements Strong customer-service orientation. Experience leading technical teams. Effective interpersonal skills for collaborating across diverse backgrounds and skill sets. Familiarity with enterprise-scale software deployment architectures. Experience or exposure to Site Reliability Engineering (SRE) principles. Willingness to contribute to internal and customer-facing documentation. Nice to Haves Experience with Apache NiFi. Experience with Elasticsearch and Kibana. Familiarity with Kubernetes. Knowledge of map-reduce analytic environments (e.g., Hadoop). Experience with frontend UI development. Production-grade software development experience in Java and Python. Experience productizing software as containers with Docker/Kubernetes. Compensation Employment Policy Salary is determined by multiple factors, including location, education, experience, skills, and organizational requirements. The projected compensation range for this position is $200,000 - $250,000 (annualized USD). Benefits Overview At Intezra, Inc., we offer a comprehensive benefits package designed to support long-term career growth and work-life balance: Three CareFirst medical plans available; Intezra pays up to 100% of healthcare premiums and up to 100% of deductibles (based on plan selection) for employees and dependents Intezra pays 100% for CareFirst Dental and Vision plans for employees and dependents 401(k): 15% company contribution (no match required) PTO: 160 hours, increasing with seniority 12 Floating Holidays 4 Code Red Days EEO Statement Intezra, Inc. provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any kind without regard to race, color, religion, age, sex, national origin, disability status, genetics, pregnancy, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. About Us Intezra Inc. is a small business prime contractor for all realms of cyber and AI/ML development, from tactical-level tools and capabilities to enterprise-level infrastructure and operations. Our leadership team and staff have helped solve the most complex challenges for the intelligence community for over 15 years. , About Intezra, Inc. Intezra Inc. is a small business prime contractor for all realms of cyber and AI/ML development, from tactical-level tools and capabilities to enterprise-level infrastructure and operations. Our leadership team and staff have helped solve the most complex challenges for the intelligence community for over 15 years.
09/26/2026
Full time
Job Description Job Description Job Description Technical Team Lead - Business Intelligence Platform Columbia, MD Full Time TS/SCI with Polygraph Required Position: Technical Team Lead (Software Engineer, Level 3) Location: Columbia, MD (on-site) Category: Software Engineering / Technical Leadership / Data Engineering Clearance Requirement: Active TS/SCI with Polygraph Compensation: $200,000 - $250,000 (annualized USD) Experience Requirement: 12+ years with a Bachelor's degree, OR 10+ years with a Master's degree, OR 4 additional years of relevant experience in lieu of a degree Description Serve as the Technical Team Lead for the Mission Intelligence (MI) team, supporting data engineering, analytics, and automation initiatives. The MI team operates a business intelligence platform that enables enterprise-wide, data-driven decision-making. Your primary responsibility is to ensure the reliability, availability, and quality of this high-impact platform. This is a leadership-leaning role with real engineering teeth: you'll mentor engineers, unblock execution, set technical direction, and quietly hold the line on quality across the platform. Responsibilities Gather stakeholder requirements, assess available data, and develop solutions for delivering key metrics. Break down complex work into actionable steps that demonstrate consistent progress. Remove technical obstacles, manage expectations, and support team execution. Define and communicate task scope through clear documentation and tracking systems. Enable the team to integrate Site Reliability Engineering practices into the operational platform. Mentor and guide junior software engineers and data scientists. Produce project management materials such as agendas, meeting notes, and design decision records. Skills Requirements Strong customer-service orientation. Experience leading technical teams. Effective interpersonal skills for collaborating across diverse backgrounds and skill sets. Familiarity with enterprise-scale software deployment architectures. Experience or exposure to Site Reliability Engineering (SRE) principles. Willingness to contribute to internal and customer-facing documentation. Nice to Haves Experience with Apache NiFi. Experience with Elasticsearch and Kibana. Familiarity with Kubernetes. Knowledge of map-reduce analytic environments (e.g., Hadoop). Experience with frontend UI development. Production-grade software development experience in Java and Python. Experience productizing software as containers with Docker/Kubernetes. Compensation Employment Policy Salary is determined by multiple factors, including location, education, experience, skills, and organizational requirements. The projected compensation range for this position is $200,000 - $250,000 (annualized USD). Benefits Overview At Intezra, Inc., we offer a comprehensive benefits package designed to support long-term career growth and work-life balance: Three CareFirst medical plans available; Intezra pays up to 100% of healthcare premiums and up to 100% of deductibles (based on plan selection) for employees and dependents Intezra pays 100% for CareFirst Dental and Vision plans for employees and dependents 401(k): 15% company contribution (no match required) PTO: 160 hours, increasing with seniority 12 Floating Holidays 4 Code Red Days EEO Statement Intezra, Inc. provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any kind without regard to race, color, religion, age, sex, national origin, disability status, genetics, pregnancy, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. About Us Intezra Inc. is a small business prime contractor for all realms of cyber and AI/ML development, from tactical-level tools and capabilities to enterprise-level infrastructure and operations. Our leadership team and staff have helped solve the most complex challenges for the intelligence community for over 15 years. , About Intezra, Inc. Intezra Inc. is a small business prime contractor for all realms of cyber and AI/ML development, from tactical-level tools and capabilities to enterprise-level infrastructure and operations. Our leadership team and staff have helped solve the most complex challenges for the intelligence community for over 15 years.
Job Description Job Description Job Description Technical Team Lead - Business Intelligence Platform Columbia, MD Full Time TS/SCI with Polygraph Required Position: Technical Team Lead (Software Engineer, Level 3) Location: Columbia, MD (on-site) Category: Software Engineering / Technical Leadership / Data Engineering Clearance Requirement: Active TS/SCI with Polygraph Compensation: $200,000 - $250,000 (annualized USD) Experience Requirement: 12+ years with a Bachelor's degree, OR 10+ years with a Master's degree, OR 4 additional years of relevant experience in lieu of a degree Description Serve as the Technical Team Lead for the Mission Intelligence (MI) team, supporting data engineering, analytics, and automation initiatives. The MI team operates a business intelligence platform that enables enterprise-wide, data-driven decision-making. Your primary responsibility is to ensure the reliability, availability, and quality of this high-impact platform. You'll also contribute to the MI team as a systems engineer, software engineer, and analytic developer - designing, developing, and integrating solutions that involve the analysis of large data sets to establish operational visibility and deliver actionable insights. Responsibilities Develop analytics to combine, normalize, and enrich large data sets. Design and implement ETL workflows to convert and normalize data. Augment the platform with new tools or technologies. Gather stakeholder requirements, assess available data, and develop solutions for delivering key metrics. Break down tasks into actionable steps that demonstrate consistent progress. Remove technical obstacles, manage expectations, and support team execution. Define and communicate task scope through clear documentation and tracking systems. Enable the team to integrate Site Reliability Engineering practices into the operational platform. Mentor and guide junior software engineers and data scientists. Produce project management materials such as agendas, meeting notes, and design decision records. Skills Requirements Experience supporting enterprise-scale platforms. Strong Java development skills. Familiarity with authentication and authorization platforms and standards. Experience with service containerization and deployment with Docker/Kubernetes. Familiarity with Git for software version control. Experience with Atlassian Tools (Jira, Confluence). Customer-service mindset. Experience leading technical teams. Effective interpersonal skills for collaborating across diverse backgrounds and skill sets. Experience or exposure to Site Reliability Engineering (SRE) principles. Willingness to contribute to internal and customer-facing documentation. Nice to Haves Experience with Apache NiFi. Experience with Elasticsearch and Kibana. Familiarity with Kubernetes. Knowledge of map-reduce analytic environments (e.g., Hadoop). Python experience. Prior experience in cyber operations or capability development. Compensation Employment Policy Salary is determined by multiple factors, including location, education, experience, skills, and organizational requirements. The projected compensation range for this position is $200,000 - $250,000 (annualized USD). Benefits Overview At Intezra, Inc., we offer a comprehensive benefits package designed to support long-term career growth and work-life balance: Three CareFirst medical plans available; Intezra pays up to 100% of healthcare premiums and up to 100% of deductibles (based on plan selection) for employees and dependents Intezra pays 100% for CareFirst Dental and Vision plans for employees and dependents 401(k): 15% company contribution (no match required) PTO: 160 hours, increasing with seniority 12 Floating Holidays 4 Code Red Days EEO Statement Intezra, Inc. provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any kind without regard to race, color, religion, age, sex, national origin, disability status, genetics, pregnancy, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. About Us Intezra Inc. is a small business prime contractor for all realms of cyber and AI/ML development, from tactical-level tools and capabilities to enterprise-level infrastructure and operations. Our leadership team and staff have helped solve the most complex challenges for the intelligence community for over 15 years. , About Intezra, Inc. Intezra Inc. is a small business prime contractor for all realms of cyber and AI/ML development, from tactical-level tools and capabilities to enterprise-level infrastructure and operations. Our leadership team and staff have helped solve the most complex challenges for the intelligence community for over 15 years.
09/26/2026
Full time
Job Description Job Description Job Description Technical Team Lead - Business Intelligence Platform Columbia, MD Full Time TS/SCI with Polygraph Required Position: Technical Team Lead (Software Engineer, Level 3) Location: Columbia, MD (on-site) Category: Software Engineering / Technical Leadership / Data Engineering Clearance Requirement: Active TS/SCI with Polygraph Compensation: $200,000 - $250,000 (annualized USD) Experience Requirement: 12+ years with a Bachelor's degree, OR 10+ years with a Master's degree, OR 4 additional years of relevant experience in lieu of a degree Description Serve as the Technical Team Lead for the Mission Intelligence (MI) team, supporting data engineering, analytics, and automation initiatives. The MI team operates a business intelligence platform that enables enterprise-wide, data-driven decision-making. Your primary responsibility is to ensure the reliability, availability, and quality of this high-impact platform. You'll also contribute to the MI team as a systems engineer, software engineer, and analytic developer - designing, developing, and integrating solutions that involve the analysis of large data sets to establish operational visibility and deliver actionable insights. Responsibilities Develop analytics to combine, normalize, and enrich large data sets. Design and implement ETL workflows to convert and normalize data. Augment the platform with new tools or technologies. Gather stakeholder requirements, assess available data, and develop solutions for delivering key metrics. Break down tasks into actionable steps that demonstrate consistent progress. Remove technical obstacles, manage expectations, and support team execution. Define and communicate task scope through clear documentation and tracking systems. Enable the team to integrate Site Reliability Engineering practices into the operational platform. Mentor and guide junior software engineers and data scientists. Produce project management materials such as agendas, meeting notes, and design decision records. Skills Requirements Experience supporting enterprise-scale platforms. Strong Java development skills. Familiarity with authentication and authorization platforms and standards. Experience with service containerization and deployment with Docker/Kubernetes. Familiarity with Git for software version control. Experience with Atlassian Tools (Jira, Confluence). Customer-service mindset. Experience leading technical teams. Effective interpersonal skills for collaborating across diverse backgrounds and skill sets. Experience or exposure to Site Reliability Engineering (SRE) principles. Willingness to contribute to internal and customer-facing documentation. Nice to Haves Experience with Apache NiFi. Experience with Elasticsearch and Kibana. Familiarity with Kubernetes. Knowledge of map-reduce analytic environments (e.g., Hadoop). Python experience. Prior experience in cyber operations or capability development. Compensation Employment Policy Salary is determined by multiple factors, including location, education, experience, skills, and organizational requirements. The projected compensation range for this position is $200,000 - $250,000 (annualized USD). Benefits Overview At Intezra, Inc., we offer a comprehensive benefits package designed to support long-term career growth and work-life balance: Three CareFirst medical plans available; Intezra pays up to 100% of healthcare premiums and up to 100% of deductibles (based on plan selection) for employees and dependents Intezra pays 100% for CareFirst Dental and Vision plans for employees and dependents 401(k): 15% company contribution (no match required) PTO: 160 hours, increasing with seniority 12 Floating Holidays 4 Code Red Days EEO Statement Intezra, Inc. provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any kind without regard to race, color, religion, age, sex, national origin, disability status, genetics, pregnancy, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. About Us Intezra Inc. is a small business prime contractor for all realms of cyber and AI/ML development, from tactical-level tools and capabilities to enterprise-level infrastructure and operations. Our leadership team and staff have helped solve the most complex challenges for the intelligence community for over 15 years. , About Intezra, Inc. Intezra Inc. is a small business prime contractor for all realms of cyber and AI/ML development, from tactical-level tools and capabilities to enterprise-level infrastructure and operations. Our leadership team and staff have helped solve the most complex challenges for the intelligence community for over 15 years.
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description While the AI innovation race in Biopharma is focused on Drug discovery, Product Development/ CMC represents the next barrier/ bottleneck. The complexity of biological systems, the rigor of regulatory expectations, the pace of pipeline growth, and the enormous value at stake make this one of the highest-leverage domains for applied data science and AI in the entire pharmaceutical value chain. We here at BTS - PDST, are building a dedicated, AI-native team that is driving cutting edge programs across early stage, late stage and commercial product development to accelerate E2E product development and launch, maximize yields of block buster products. Through our deep collaboration with PDST scientists we are boldly reimagining how Abbvie can bring our pipeline products and lifesaving drugs to patients faster, safer and in cost effective manner fueled by AI. Principal Data Engineer is a highly technical, AI-native role responsible for designing, building, and operating production-grade data pipelines and data products that power AI/ML, analytics, and automation across AbbVie's CMC and manufacturing ecosystem. This role is embedded inside PDST and works at the frontier of pharmaceutical data engineering. You will integrate and harmonize data from the full spectrum of manufacturing and development systems - including MES, historians, LIMS, QMS, ERP, and instrument platforms - and transform it into reliable, governed, semantically rich data assets that data scientists, process engineers, and AI systems can actually use. Enterprise-scale scope: Enterprise-scale biologics portfolio spanning clinical, commercial, and lifecycle stages Building AI playbook for the future: First-in-AbbVie and first-in-biologics analytical approaches; you build the AI playbook for the future Growth and Impact: Direct impact on regulatory submissions, commercial readiness, and manufacturing decisions through deep cross-functional exposure to manufacturing, quality, regulatory, and scientific leadership Mission: Every model you build helps ensure safe, reliable medicines reach patients at scale Responsibilities Data Ingestion & Integration Design and implement scalable, robust data ingestion pipelines that connect CMC and manufacturing source systems - including MES (Manufacturing Execution Systems), process historians, LIMS, QMS, ERP platforms, and instrument data sources - to centralized and federated data environments. Build connectors, adapters, and integration layers that handle the heterogeneous data formats, protocols, and latency profiles characteristic of pharmaceutical manufacturing environments. Support both batch and real-time/streaming data patterns, selecting appropriate architectures based on use case requirements. Data Harmonization & Semantic Modeling Develop and maintain harmonized data models and ontologies that bring consistency to CMC and manufacturing data across sites, systems, and modalities. Execute semantic mapping efforts that align source system fields, units, and identifiers to enterprise data standards and scientific meaning. Collaborate with process scientists, analytical chemists, and manufacturing engineers to ensure data models accurately reflect domain reality. Data Quality, Observability & Governance Implement automated data quality controls, validation frameworks, and anomaly detection mechanisms across pipeline layers. Build and maintain data lineage documentation and metadata infrastructure, enabling full traceability from source system to AI model input. Establish pipeline observability practices - monitoring, alerting, SLA tracking - to ensure data product reliability in production. Support data governance practices aligned with GxP requirements, 21 CFR Part 11, and AbbVie data standards. AI/ML Enablement & Data Product Development Architect and deliver governed, versioned, reusable data products purpose-built for AI/ML consumption, including feature stores, curated datasets, and vector-ready data layers for RAG and LLM applications. Partner closely with data scientists, ML engineers, and process modelers to understand model data requirements and translate them into reliable, scalable data infrastructure. Accelerate AI program delivery by eliminating data bottlenecks - not by workarounds, but by solving root causes structurally. Platform & Operational Enablement Contribute to the design and evolution of PDST's cloud-based data platform, including lakehouse architecture, data cataloging, access control, and compute infrastructure. Write and maintain infrastructure-as-code, CI/CD pipelines, and automated testing frameworks for data systems. Support platform onboarding of new CMC data domains and manufacturing sites, ensuring consistent application of standards and patterns. Provide operational support for production data pipelines, maintaining uptime and data freshness commitments. Stakeholder Engagement & Scientific Leadership Influence technical decision-making without formal authority - earning trust through scientific rigor, transparent methodology, and demonstrated business impact. Qualifications Required: Bachelor's Degree Computer Science, Data Engineering, Information Systems, Software Engineering, Bioinformatics, or a closely related technical field plus 6 years' experience; Master's Degree plus 5 years' experience; PhD plus 0 years' experience. Respective years of hands-on experience designing and building enterprise-grade data pipelines, integration workflows, and data products in complex, multi-source environments. Expert-level proficiency in Python for data engineering tasks - pipeline development, transformation logic, data validation, and automation. Strong SQL skills across modern analytical and transactional databases; comfort with both ANSI SQL and platform-specific dialects. Demonstrated experience with cloud data platforms (AWS, Azure, or GCP) and modern data stack components - including tools such as dbt, Spark, Airflow, Databricks, Snowflake, or equivalents. Develop ETL/ELT pipelines using tools such as Informatica, Talend, Apache NiFi, and cloud-native services (e.g., AWS Glue, Azure Data Factory). Implement master data management (MDM), metadata management, and data cataloging solutions to ensure proper data lineage, accessibility, and compliance. Set and enforce standards for API development and data integration (REST, GraphQL, OData), enabling seamless integration using microservices architectures. Ownership orientation: you define your own problem space, drive solutions to completion, and hold yourself accountable to outcomes - not just outputs. Solution-architect instinct: you think before you build, consider the full landscape of available approaches, and choose tools based on fit-for-purpose reasoning rather than familiarity or trend. Scientific integrity: you build models you can explain, defend, and improve - and you apply the same standard to the work of others. Influence through credibility: you earn the confidence of scientists, engineers, and quality professionals by being right, being clear, and being useful - not by title or volume. Bias for impact: you are drawn to problems where the stakes are high and the analytical opportunity is real, and you are energized rather than intimidated by ambiguity. Preferred: 3+ years of hands-on experience designing and building enterprise-grade data pipelines, integration workflows, and data products in complex, multi-source environments. Familiarity with technology transfer workflows, process characterization study design, or commercial process validation (PPQ/PV) in a biologics or pharmaceutical context. Experience in pharmaceutical, biotech, or other regulated life sciences manufacturing environments. Familiarity with GxP data principles, 21 CFR Part 11 compliance, or data integrity requirements in regulated industries. Prior exposure to manufacturing source systems such as MES, process historians (e.g., OSIsoft PI/AVEVA), LIMS, QMS, or ERP platforms Experience building data infrastructure for AI/ML programs - including feature engineering pipelines, model training datasets, or vector/embedding data layers for RAG architectures. Knowledge of biologics manufacturing processes (e.g., upstream cell culture, downstream purification, fill-finish) or CMC development workflows. Familiarity with data mesh, data fabric, or federated data architecture patterns. Experience with graph databases, knowledge graphs, or ontology frameworks applied to scientific or manufacturing data. Contributions to open-source data tooling or demonstrated engagement with the modern data engineering community. Design logical, physical, and conceptual data models using modeling tools (e.g., Erwin, PowerDesigner, dbt). . click apply for full job details
09/26/2026
Full time
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description While the AI innovation race in Biopharma is focused on Drug discovery, Product Development/ CMC represents the next barrier/ bottleneck. The complexity of biological systems, the rigor of regulatory expectations, the pace of pipeline growth, and the enormous value at stake make this one of the highest-leverage domains for applied data science and AI in the entire pharmaceutical value chain. We here at BTS - PDST, are building a dedicated, AI-native team that is driving cutting edge programs across early stage, late stage and commercial product development to accelerate E2E product development and launch, maximize yields of block buster products. Through our deep collaboration with PDST scientists we are boldly reimagining how Abbvie can bring our pipeline products and lifesaving drugs to patients faster, safer and in cost effective manner fueled by AI. Principal Data Engineer is a highly technical, AI-native role responsible for designing, building, and operating production-grade data pipelines and data products that power AI/ML, analytics, and automation across AbbVie's CMC and manufacturing ecosystem. This role is embedded inside PDST and works at the frontier of pharmaceutical data engineering. You will integrate and harmonize data from the full spectrum of manufacturing and development systems - including MES, historians, LIMS, QMS, ERP, and instrument platforms - and transform it into reliable, governed, semantically rich data assets that data scientists, process engineers, and AI systems can actually use. Enterprise-scale scope: Enterprise-scale biologics portfolio spanning clinical, commercial, and lifecycle stages Building AI playbook for the future: First-in-AbbVie and first-in-biologics analytical approaches; you build the AI playbook for the future Growth and Impact: Direct impact on regulatory submissions, commercial readiness, and manufacturing decisions through deep cross-functional exposure to manufacturing, quality, regulatory, and scientific leadership Mission: Every model you build helps ensure safe, reliable medicines reach patients at scale Responsibilities Data Ingestion & Integration Design and implement scalable, robust data ingestion pipelines that connect CMC and manufacturing source systems - including MES (Manufacturing Execution Systems), process historians, LIMS, QMS, ERP platforms, and instrument data sources - to centralized and federated data environments. Build connectors, adapters, and integration layers that handle the heterogeneous data formats, protocols, and latency profiles characteristic of pharmaceutical manufacturing environments. Support both batch and real-time/streaming data patterns, selecting appropriate architectures based on use case requirements. Data Harmonization & Semantic Modeling Develop and maintain harmonized data models and ontologies that bring consistency to CMC and manufacturing data across sites, systems, and modalities. Execute semantic mapping efforts that align source system fields, units, and identifiers to enterprise data standards and scientific meaning. Collaborate with process scientists, analytical chemists, and manufacturing engineers to ensure data models accurately reflect domain reality. Data Quality, Observability & Governance Implement automated data quality controls, validation frameworks, and anomaly detection mechanisms across pipeline layers. Build and maintain data lineage documentation and metadata infrastructure, enabling full traceability from source system to AI model input. Establish pipeline observability practices - monitoring, alerting, SLA tracking - to ensure data product reliability in production. Support data governance practices aligned with GxP requirements, 21 CFR Part 11, and AbbVie data standards. AI/ML Enablement & Data Product Development Architect and deliver governed, versioned, reusable data products purpose-built for AI/ML consumption, including feature stores, curated datasets, and vector-ready data layers for RAG and LLM applications. Partner closely with data scientists, ML engineers, and process modelers to understand model data requirements and translate them into reliable, scalable data infrastructure. Accelerate AI program delivery by eliminating data bottlenecks - not by workarounds, but by solving root causes structurally. Platform & Operational Enablement Contribute to the design and evolution of PDST's cloud-based data platform, including lakehouse architecture, data cataloging, access control, and compute infrastructure. Write and maintain infrastructure-as-code, CI/CD pipelines, and automated testing frameworks for data systems. Support platform onboarding of new CMC data domains and manufacturing sites, ensuring consistent application of standards and patterns. Provide operational support for production data pipelines, maintaining uptime and data freshness commitments. Stakeholder Engagement & Scientific Leadership Influence technical decision-making without formal authority - earning trust through scientific rigor, transparent methodology, and demonstrated business impact. Qualifications Required: Bachelor's Degree Computer Science, Data Engineering, Information Systems, Software Engineering, Bioinformatics, or a closely related technical field plus 6 years' experience; Master's Degree plus 5 years' experience; PhD plus 0 years' experience. Respective years of hands-on experience designing and building enterprise-grade data pipelines, integration workflows, and data products in complex, multi-source environments. Expert-level proficiency in Python for data engineering tasks - pipeline development, transformation logic, data validation, and automation. Strong SQL skills across modern analytical and transactional databases; comfort with both ANSI SQL and platform-specific dialects. Demonstrated experience with cloud data platforms (AWS, Azure, or GCP) and modern data stack components - including tools such as dbt, Spark, Airflow, Databricks, Snowflake, or equivalents. Develop ETL/ELT pipelines using tools such as Informatica, Talend, Apache NiFi, and cloud-native services (e.g., AWS Glue, Azure Data Factory). Implement master data management (MDM), metadata management, and data cataloging solutions to ensure proper data lineage, accessibility, and compliance. Set and enforce standards for API development and data integration (REST, GraphQL, OData), enabling seamless integration using microservices architectures. Ownership orientation: you define your own problem space, drive solutions to completion, and hold yourself accountable to outcomes - not just outputs. Solution-architect instinct: you think before you build, consider the full landscape of available approaches, and choose tools based on fit-for-purpose reasoning rather than familiarity or trend. Scientific integrity: you build models you can explain, defend, and improve - and you apply the same standard to the work of others. Influence through credibility: you earn the confidence of scientists, engineers, and quality professionals by being right, being clear, and being useful - not by title or volume. Bias for impact: you are drawn to problems where the stakes are high and the analytical opportunity is real, and you are energized rather than intimidated by ambiguity. Preferred: 3+ years of hands-on experience designing and building enterprise-grade data pipelines, integration workflows, and data products in complex, multi-source environments. Familiarity with technology transfer workflows, process characterization study design, or commercial process validation (PPQ/PV) in a biologics or pharmaceutical context. Experience in pharmaceutical, biotech, or other regulated life sciences manufacturing environments. Familiarity with GxP data principles, 21 CFR Part 11 compliance, or data integrity requirements in regulated industries. Prior exposure to manufacturing source systems such as MES, process historians (e.g., OSIsoft PI/AVEVA), LIMS, QMS, or ERP platforms Experience building data infrastructure for AI/ML programs - including feature engineering pipelines, model training datasets, or vector/embedding data layers for RAG architectures. Knowledge of biologics manufacturing processes (e.g., upstream cell culture, downstream purification, fill-finish) or CMC development workflows. Familiarity with data mesh, data fabric, or federated data architecture patterns. Experience with graph databases, knowledge graphs, or ontology frameworks applied to scientific or manufacturing data. Contributions to open-source data tooling or demonstrated engagement with the modern data engineering community. Design logical, physical, and conceptual data models using modeling tools (e.g., Erwin, PowerDesigner, dbt). . click apply for full job details
Institute of Foundation Models
Sunnyvale, California
Job Description Job Description About the Institute of Foundation Models The Institute of Foundation Models is a dedicated research lab focused on building, understanding, using, and risk-managing foundation models. Our mission is to advance AI research, support the next generation of AI builders, and develop impactful systems that improve how frontier models are trained, evaluated, deployed, and governed. As part of our team, you will work closely with researchers, machine learning engineers, data scientists, software engineers, and product teams on some of the most important challenges in AI development. You will contribute to systems that help measure model quality, identify failure modes, and improve the reliability, safety, and readiness of model releases. The Role We are looking for an Eval360 - Error Analysis Engineer to help build, improve, and operate Eval360, an evaluation service that serves as a quality gate for AI models. This person will focus specifically on error analysis : understanding where models fail, why they fail, how those failures should be categorized, and how evaluation systems can better detect, measure, and prevent these issues before models are released. You will collaborate with researchers, machine learning engineers, product managers, data scientists, and platform teams to develop AI evaluation applications and internal tools based on next-generation AI research. You will be part of a cross-functional team responsible for the full software development lifecycle, from requirements gathering and system design to implementation, deployment, monitoring, debugging, documentation, and continuous improvement. The ideal candidate is comfortable working across the stack, including front-end interfaces for reviewing errors, back-end evaluation pipelines, data analysis workflows, model evaluation infrastructure, databases, dashboards, and APIs. This person should have strong software engineering skills, excellent analytical judgment, and the ability to turn ambiguous model failures into structured insights that improve evaluation quality. Key Responsibilities • Collaborate with researchers, machine learning engineers, data scientists, product managers, and internal stakeholders to implement innovative software solutions for Eval360 and related model evaluation workflows. • Build and improve Eval360 as an evaluation service that acts as a quality gate for model development, model comparison, and model release decisions. • Perform deep error analysis on model outputs, including identifying failure patterns, categorizing issues, tracing root causes, and proposing improvements to evaluation methodology. • Develop tools, workflows, and dashboards that make it easier for researchers and engineers to inspect model failures, compare model behavior, and understand quality regressions. • Design and implement client-side and server-side architecture for evaluation review systems, error analysis interfaces, reporting tools, and internal evaluation applications. • Develop responsive, usable interfaces that support error triage, annotation review, evaluation debugging, and model quality investigation. • Build and maintain back-end services, APIs, data pipelines, and integrations that support evaluation execution, results storage, analysis, and reporting. • Test software to ensure responsiveness, correctness, reliability, and efficiency across evaluation workflows. • Troubleshoot, debug, and upgrade evaluation systems, including identifying issues in data processing, evaluation metrics, model output handling, job orchestration, and user-facing analysis tools. • Create and maintain security, access control, and data protection settings for evaluation data, model outputs, annotations, and internal tooling. • Write clear technical documentation for Eval360 systems, error taxonomies, evaluation workflows, debugging procedures, and user-facing tools. • Work with researchers, data scientists, analysts, and machine learning engineers to improve evaluation quality, model diagnostics, and failure-mode visibility. • Keep track of new development tools, evaluation frameworks, model analysis methods, data quality techniques, and architectures relevant to AI evaluation systems. • Contribute to the design of error taxonomies, evaluation rubrics, quality thresholds, regression detection methods, and model readiness criteria. • Help ensure Eval360 produces reliable, interpretable, and actionable signals for model quality gates. • Contribute to research publications, technical reports, internal knowledge sharing, and external presentations where appropriate. • Contribute to intellectual property and thought leadership in AI evaluation, error analysis, model quality measurement, and evaluation infrastructure. • Perform all other duties as reasonably directed by the line manager that are aligned with these functional objectives. Academic Qualifications • Bachelor's degree in Computer Science, Machine Learning, Data Science, Software Engineering, Statistics, or a related technical field required. • Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field preferred. Professional Experience • Proven experience as a Software Engineer, Full Stack Developer, Machine Learning Evaluation Engineer, Data Scientist, AI Engineer, or similar role. • Experience building software systems for AI, machine learning, data analysis, evaluation, annotation, experimentation, or model monitoring. • Experience working with AI algorithms and the ability to develop systems that accommodate AI-related requirements. • Experience performing error analysis, model evaluation, data quality analysis, or failure-mode investigation for machine learning or language model systems. • Experience developing internal applications, dashboards, review tools, or web-based workflows for technical users. • Familiarity with common software stacks, including front-end frameworks, back-end services, databases, APIs, and cloud or internal infrastructure. • Familiarity with GitHub, Git, CI/CD workflows, and collaborative software development practices. • Knowledge of front-end languages and libraries such as HTML, CSS, JavaScript, TypeScript, React, Angular, or similar technologies. • Knowledge of back-end languages and frameworks such as Python, Java, C#, Node.js, FastAPI, Flask, Django, or similar technologies. • Familiarity with databases such as MySQL, PostgreSQL, MongoDB, or other structured and unstructured data stores. • Familiarity with evaluation frameworks, experiment tracking systems, data pipelines, or machine learning infrastructure is strongly preferred. • Ability to analyze complex model outputs and translate qualitative failures into structured, measurable categories. • Strong problem-solving and troubleshooting skills, especially for ambiguous technical issues involving models, data, metrics, and software systems. • Effective communication and collaboration skills, with the ability to work across research, engineering, data, and product teams. • Strong attention to detail and a high bar for evaluation quality, reliability, and interpretability. Preferred Qualifications • Experience with large language models, foundation models, multimodal models, or model evaluation systems. • Experience designing or using error taxonomies, evaluation rubrics, benchmark datasets, human evaluation workflows, or automated grading systems. • Experience with Python-based data analysis tools such as pandas, NumPy, Jupyter, or similar. • Experience with visualization or dashboarding tools for model quality analysis. • Experience with distributed systems, job queues, workflow orchestration, or large-scale data processing. • Experience working in a research environment or with fast-moving AI product and model teams. Salary Range The posted salary range represents the company's good faith estimate of the compensation for this position upon hire. The actual compensation offered may vary within this range depending on individual qualifications, including but not limited to relevant skills, experience, education, certifications, geographic location, and specific business needs. Visa Sponsorship This position is eligible for visa sponsorship. Benefits Include • Comprehensive medical, dental, and vision benefits • Bonus • 401K plan • Generous paid time off, sick leave, and holidays • Paid parental leave • Employee assistance program • Life insurance and disability insurance
09/26/2026
Full time
Job Description Job Description About the Institute of Foundation Models The Institute of Foundation Models is a dedicated research lab focused on building, understanding, using, and risk-managing foundation models. Our mission is to advance AI research, support the next generation of AI builders, and develop impactful systems that improve how frontier models are trained, evaluated, deployed, and governed. As part of our team, you will work closely with researchers, machine learning engineers, data scientists, software engineers, and product teams on some of the most important challenges in AI development. You will contribute to systems that help measure model quality, identify failure modes, and improve the reliability, safety, and readiness of model releases. The Role We are looking for an Eval360 - Error Analysis Engineer to help build, improve, and operate Eval360, an evaluation service that serves as a quality gate for AI models. This person will focus specifically on error analysis : understanding where models fail, why they fail, how those failures should be categorized, and how evaluation systems can better detect, measure, and prevent these issues before models are released. You will collaborate with researchers, machine learning engineers, product managers, data scientists, and platform teams to develop AI evaluation applications and internal tools based on next-generation AI research. You will be part of a cross-functional team responsible for the full software development lifecycle, from requirements gathering and system design to implementation, deployment, monitoring, debugging, documentation, and continuous improvement. The ideal candidate is comfortable working across the stack, including front-end interfaces for reviewing errors, back-end evaluation pipelines, data analysis workflows, model evaluation infrastructure, databases, dashboards, and APIs. This person should have strong software engineering skills, excellent analytical judgment, and the ability to turn ambiguous model failures into structured insights that improve evaluation quality. Key Responsibilities • Collaborate with researchers, machine learning engineers, data scientists, product managers, and internal stakeholders to implement innovative software solutions for Eval360 and related model evaluation workflows. • Build and improve Eval360 as an evaluation service that acts as a quality gate for model development, model comparison, and model release decisions. • Perform deep error analysis on model outputs, including identifying failure patterns, categorizing issues, tracing root causes, and proposing improvements to evaluation methodology. • Develop tools, workflows, and dashboards that make it easier for researchers and engineers to inspect model failures, compare model behavior, and understand quality regressions. • Design and implement client-side and server-side architecture for evaluation review systems, error analysis interfaces, reporting tools, and internal evaluation applications. • Develop responsive, usable interfaces that support error triage, annotation review, evaluation debugging, and model quality investigation. • Build and maintain back-end services, APIs, data pipelines, and integrations that support evaluation execution, results storage, analysis, and reporting. • Test software to ensure responsiveness, correctness, reliability, and efficiency across evaluation workflows. • Troubleshoot, debug, and upgrade evaluation systems, including identifying issues in data processing, evaluation metrics, model output handling, job orchestration, and user-facing analysis tools. • Create and maintain security, access control, and data protection settings for evaluation data, model outputs, annotations, and internal tooling. • Write clear technical documentation for Eval360 systems, error taxonomies, evaluation workflows, debugging procedures, and user-facing tools. • Work with researchers, data scientists, analysts, and machine learning engineers to improve evaluation quality, model diagnostics, and failure-mode visibility. • Keep track of new development tools, evaluation frameworks, model analysis methods, data quality techniques, and architectures relevant to AI evaluation systems. • Contribute to the design of error taxonomies, evaluation rubrics, quality thresholds, regression detection methods, and model readiness criteria. • Help ensure Eval360 produces reliable, interpretable, and actionable signals for model quality gates. • Contribute to research publications, technical reports, internal knowledge sharing, and external presentations where appropriate. • Contribute to intellectual property and thought leadership in AI evaluation, error analysis, model quality measurement, and evaluation infrastructure. • Perform all other duties as reasonably directed by the line manager that are aligned with these functional objectives. Academic Qualifications • Bachelor's degree in Computer Science, Machine Learning, Data Science, Software Engineering, Statistics, or a related technical field required. • Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field preferred. Professional Experience • Proven experience as a Software Engineer, Full Stack Developer, Machine Learning Evaluation Engineer, Data Scientist, AI Engineer, or similar role. • Experience building software systems for AI, machine learning, data analysis, evaluation, annotation, experimentation, or model monitoring. • Experience working with AI algorithms and the ability to develop systems that accommodate AI-related requirements. • Experience performing error analysis, model evaluation, data quality analysis, or failure-mode investigation for machine learning or language model systems. • Experience developing internal applications, dashboards, review tools, or web-based workflows for technical users. • Familiarity with common software stacks, including front-end frameworks, back-end services, databases, APIs, and cloud or internal infrastructure. • Familiarity with GitHub, Git, CI/CD workflows, and collaborative software development practices. • Knowledge of front-end languages and libraries such as HTML, CSS, JavaScript, TypeScript, React, Angular, or similar technologies. • Knowledge of back-end languages and frameworks such as Python, Java, C#, Node.js, FastAPI, Flask, Django, or similar technologies. • Familiarity with databases such as MySQL, PostgreSQL, MongoDB, or other structured and unstructured data stores. • Familiarity with evaluation frameworks, experiment tracking systems, data pipelines, or machine learning infrastructure is strongly preferred. • Ability to analyze complex model outputs and translate qualitative failures into structured, measurable categories. • Strong problem-solving and troubleshooting skills, especially for ambiguous technical issues involving models, data, metrics, and software systems. • Effective communication and collaboration skills, with the ability to work across research, engineering, data, and product teams. • Strong attention to detail and a high bar for evaluation quality, reliability, and interpretability. Preferred Qualifications • Experience with large language models, foundation models, multimodal models, or model evaluation systems. • Experience designing or using error taxonomies, evaluation rubrics, benchmark datasets, human evaluation workflows, or automated grading systems. • Experience with Python-based data analysis tools such as pandas, NumPy, Jupyter, or similar. • Experience with visualization or dashboarding tools for model quality analysis. • Experience with distributed systems, job queues, workflow orchestration, or large-scale data processing. • Experience working in a research environment or with fast-moving AI product and model teams. Salary Range The posted salary range represents the company's good faith estimate of the compensation for this position upon hire. The actual compensation offered may vary within this range depending on individual qualifications, including but not limited to relevant skills, experience, education, certifications, geographic location, and specific business needs. Visa Sponsorship This position is eligible for visa sponsorship. Benefits Include • Comprehensive medical, dental, and vision benefits • Bonus • 401K plan • Generous paid time off, sick leave, and holidays • Paid parental leave • Employee assistance program • Life insurance and disability insurance
What Makes a Honda, is Who makes a Honda Honda has a clear vision for the future, and it's a joyful one. We are looking for individuals with the skills, courage, persistence, and dreams that will help us reach our future-focused goals. At our core is innovation. Honda is constantly innovating and developing solutions to drive our business with record success. We strive to be a company that serves as a source of "power" that supports people around the world who are trying to do things based on their own initiative and that helps people expand their own potential. To this end, Honda strives to realize "the joy and freedom of mobility" by developing new technologies and an innovative approach to achieve a "zero environmental footprint." We are looking for qualified individuals with diverse backgrounds, experiences, continuous improvement values, and a strong work ethic to join our team. If your goals and values align with Honda's, we want you to join our team to Bring the Future! Job Purpose The Data and Solution Architect is responsible for defining, governing, and advancing the enterprise data architecture required to enable scalable, trusted, and responsible AI solutions in the AI Hub. This role ensures that data platforms, models, standards, and semantic structures are designed to support AI/ML, Generative AI, Agentic AI, experimentation (POCs), and production deployment, while aligning with enterprise data governance, security, and compliance requirements. Key Accountabilities AI Ready Data Architecture & Design Lead the design of logical, physical, and semantic data architectures to support AI, advanced analytics, GenAI and Agentic AI use cases Define AI ready data models, feature oriented structures, and analytics ready data assets aligned to enterprise data platforms Ensure architectural alignment between data platforms, AI tooling, and MLOps pipelines Support design and governance of the Foundry Ontology layer as the enterprise semantic backbone for AI use cases Data Standards, Governance & Semantics Work closely with Data Architecture and Governance teams, define and enforce data standards, metadata practices, naming conventions, and master/reference data patterns for AI use cases Establish and maintain semantic consistency (business definitions, critical data elements, feature definitions) to enable explainable and reusable AI Partner with Data Governance, Legal, and Compliance teams to ensure responsible and compliant AI data usage AI Use Case Enablement & POC Support Architect data flows and patterns supporting AI POCs, experimentation environments, and sandbox platforms Guide data sourcing, profiling, and readiness activities for AI Data Scientists, Data and AI Engineers Own the data architecture stage-gate process across POC, expanded pilot, and production phases; define and maintain AI-readiness scorecards to assess data asset maturity at each stage Data Platform, Integration and Solution Architecture Architect integrations across source systems, data platforms, analytics tools, and AI services Evaluate and onboard new data sources and technologies to meet evolving AI requirements Define reference architecture and architectural guardrails for cloud, hybrid, and global deployments Lead/support solution architecture development for projects/products, where necessary Collaboration, Review & Enablement Serve as a data and solution architecture authority for AI related initiatives and design reviews Mentor junior architects, data engineers and provide architectural guidance to delivery teams Contribute to AI Hub (COE), communities of practice, standards bodies, and architecture review forums Qualifications, Experience, and Skills Bachelor's degree in Computer Science, Information Systems, Data Engineering/ Data Science, or related field 8+ years of experience in data architecture, solution architecture, enterprise data platforms, or analytics architecture Demonstrated experience supporting AI/ML, advanced analytics, or data driven product initiatives Experience operating in federated governance or hub and spoke operating models Experience with data profiling and data quality management Workstyle This is an onsite job. One remote workday per week, may be possible with prior departmental approval. Visa sponsorship issues This position is not eligible for work visa sponsorship What differentiates Honda and makes us an employer of choice? Total Rewards: Competitive Base Salary (pay will be based on several variables that include, but not limited to geographic location, work experience, etc.) Regional Bonus (when applicable) Manager Lease Car Program (No Cost - Car, Maintenance, and Insurance included) Industry-leading Benefit Plans (Medical, Dental, Vision, Rx) Paid time off, including vacation, holidays, shutdown Company Paid Short-Term and Long-Term Disability 401K Plan with company match + additional contribution Relocation assistance (if eligible) Career Growth: Advancement Opportunities Career Mobility Education Reimbursement for Continued learning Training and Development Programs Additional Offerings: Lifestyle Account Childcare Reimbursement Account Elder Care Support Tuition Assistance & Student Loan Repayment Wellbeing Program Community Service and Engagement Programs Product Programs Honda is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.
09/25/2026
Full time
What Makes a Honda, is Who makes a Honda Honda has a clear vision for the future, and it's a joyful one. We are looking for individuals with the skills, courage, persistence, and dreams that will help us reach our future-focused goals. At our core is innovation. Honda is constantly innovating and developing solutions to drive our business with record success. We strive to be a company that serves as a source of "power" that supports people around the world who are trying to do things based on their own initiative and that helps people expand their own potential. To this end, Honda strives to realize "the joy and freedom of mobility" by developing new technologies and an innovative approach to achieve a "zero environmental footprint." We are looking for qualified individuals with diverse backgrounds, experiences, continuous improvement values, and a strong work ethic to join our team. If your goals and values align with Honda's, we want you to join our team to Bring the Future! Job Purpose The Data and Solution Architect is responsible for defining, governing, and advancing the enterprise data architecture required to enable scalable, trusted, and responsible AI solutions in the AI Hub. This role ensures that data platforms, models, standards, and semantic structures are designed to support AI/ML, Generative AI, Agentic AI, experimentation (POCs), and production deployment, while aligning with enterprise data governance, security, and compliance requirements. Key Accountabilities AI Ready Data Architecture & Design Lead the design of logical, physical, and semantic data architectures to support AI, advanced analytics, GenAI and Agentic AI use cases Define AI ready data models, feature oriented structures, and analytics ready data assets aligned to enterprise data platforms Ensure architectural alignment between data platforms, AI tooling, and MLOps pipelines Support design and governance of the Foundry Ontology layer as the enterprise semantic backbone for AI use cases Data Standards, Governance & Semantics Work closely with Data Architecture and Governance teams, define and enforce data standards, metadata practices, naming conventions, and master/reference data patterns for AI use cases Establish and maintain semantic consistency (business definitions, critical data elements, feature definitions) to enable explainable and reusable AI Partner with Data Governance, Legal, and Compliance teams to ensure responsible and compliant AI data usage AI Use Case Enablement & POC Support Architect data flows and patterns supporting AI POCs, experimentation environments, and sandbox platforms Guide data sourcing, profiling, and readiness activities for AI Data Scientists, Data and AI Engineers Own the data architecture stage-gate process across POC, expanded pilot, and production phases; define and maintain AI-readiness scorecards to assess data asset maturity at each stage Data Platform, Integration and Solution Architecture Architect integrations across source systems, data platforms, analytics tools, and AI services Evaluate and onboard new data sources and technologies to meet evolving AI requirements Define reference architecture and architectural guardrails for cloud, hybrid, and global deployments Lead/support solution architecture development for projects/products, where necessary Collaboration, Review & Enablement Serve as a data and solution architecture authority for AI related initiatives and design reviews Mentor junior architects, data engineers and provide architectural guidance to delivery teams Contribute to AI Hub (COE), communities of practice, standards bodies, and architecture review forums Qualifications, Experience, and Skills Bachelor's degree in Computer Science, Information Systems, Data Engineering/ Data Science, or related field 8+ years of experience in data architecture, solution architecture, enterprise data platforms, or analytics architecture Demonstrated experience supporting AI/ML, advanced analytics, or data driven product initiatives Experience operating in federated governance or hub and spoke operating models Experience with data profiling and data quality management Workstyle This is an onsite job. One remote workday per week, may be possible with prior departmental approval. Visa sponsorship issues This position is not eligible for work visa sponsorship What differentiates Honda and makes us an employer of choice? Total Rewards: Competitive Base Salary (pay will be based on several variables that include, but not limited to geographic location, work experience, etc.) Regional Bonus (when applicable) Manager Lease Car Program (No Cost - Car, Maintenance, and Insurance included) Industry-leading Benefit Plans (Medical, Dental, Vision, Rx) Paid time off, including vacation, holidays, shutdown Company Paid Short-Term and Long-Term Disability 401K Plan with company match + additional contribution Relocation assistance (if eligible) Career Growth: Advancement Opportunities Career Mobility Education Reimbursement for Continued learning Training and Development Programs Additional Offerings: Lifestyle Account Childcare Reimbursement Account Elder Care Support Tuition Assistance & Student Loan Repayment Wellbeing Program Community Service and Engagement Programs Product Programs Honda is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.
