10 jobs found

Job Description AI Architect - Telecom Domain Job Overview We are seeking an experienced AI Architect with deep expertise in the Telecom domain to design and implement next-generation AI solutions. The ideal candidate will have strong knowledge of telecom networks, AI/ML architectures, cloud platforms, and enterprise-scale solution design. This role involves leading AI initiatives, building intelligent copilots and agents, driving innovation, and supporting strategic business transformation programs. Key Responsibilities Design and architect AI-powered assistants, copilots, and agentic AI solutions for telecom operations and engineering teams. Develop intelligent solutions for incident management, root cause analysis (RCA), anomaly detection, predictive maintenance, and operational automation. Build and integrate AI platforms using LLMs, RAG, Knowledge Graphs, Vector Databases, and Multi-Agent Systems. Lead AI product development, accelerators, proofs of concept (PoCs), and enterprise AI initiatives. Integrate structured and unstructured data from network telemetry, documentation, OSS/BSS platforms, and operational systems. Establish AI governance, security, observability, and responsible AI standards. Mentor cross-functional teams including AI Engineers, Data Scientists, Data Engineers, and Software Developers. Support client solutioning, executive presentations, proposals, and AI transformation engagements. Required Skills Strong Telecom domain expertise in RAN, Core Networks, Transport, OSS/BSS, Service Assurance, and Network Operations. Hands-on experience with LLMs, Agentic AI, RAG, Knowledge Graphs, Vector Databases, and AI Orchestration Frameworks. Expertise in Azure, Databricks, Microsoft Fabric, Snowflake, MLOps, LLMOps, APIs, and Microservices. Experience building AI solutions for network intelligence, automation, and operational analytics. Strong leadership, stakeholder management, and enterprise architecture experience.

Job Description Data Scientist Location - Louisville, KY ( Onsite) Job Summary The Data Scientist is responsible for applying advanced analytics, statistical modeling, and machine learning techniques to solve business problems and improve outcomes across Humana. This role partners with business, product, engineering, and architecture teams to develop data-driven solutions that support enterprise strategies while aligning to Humana's data security, governance, and architecture standards. Key Responsibilities Analyze large, complex datasets to identify trends, risks, opportunities, and actionable insights. Build, validate, and deploy statistical, predictive, and machine learning models. Translate business problems into analytical approaches and measurable outcomes. Partner with Data Engineers, Application Architects, Product Managers, and business stakeholders to design scalable analytics solutions. Develop experiments, forecasting models, segmentation methods, and decision-support tools. Communicate findings through dashboards, visualizations, presentations, and technical documentation. Support model monitoring, performance evaluation, and continuous improvement. Ensure solutions align with enterprise data architecture, reference standards, and approved technology patterns. Follow Humana policies for information protection, least-privilege access, secure storage, and confidential data handling. Contribute to reusable analytics assets, standards, and best practices across teams. Required Qualifications Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, Economics, or related field. Experience in data science, advanced analytics, or machine learning. Strong knowledge of: Python and/or R SQL Statistics and hypothesis testing Machine learning methods Data wrangling and feature engineering Experience working with cloud or enterprise analytics platforms. Ability to communicate technical results to non-technical stakeholders. Experience working with cross-functional teams in a regulated or enterprise environment. Preferred Qualifications Master's or PhD in a quantitative field. Experience with Databricks, Spark, or large-scale distributed data platforms. Experience in healthcare, payer, claims, member, provider, or clinical analytics. Familiarity with MLOps, model governance, and production model deployment. Experience with BI and visualization tools such as Power BI or Tableau. Understanding of data architecture, cataloging, and enterprise data standards. Technical Skills Programming: Python, R, SQL Data Platforms: Databricks, Spark, cloud data platforms Modeling: regression, classification, clustering, time series, NLP, experimentation Visualization: dashboards, storytelling, exploratory analysis Data Management: data dictionaries, data models, schema awareness, governed datasets

Job Description Senior Data Scientist Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work Institute and recognized as a 'Cool Vendor' and a 'Vendor to Watch' by Gartner. Please visit Fractal Intelligence for Imagination for more information about Fractal Location: New York City, NY (On-site) Note: This position is not eligible for Immigration Sponsorship at this time. Position Overview: We are seeking a highly motivated and analytical Senior Data Scientist with 4-6 years of experience in Machine Learning, Statistical Modeling, Predictive Analytics, and Data Science solutions. The ideal candidate will leverage advanced analytical techniques to extract insights from large and complex datasets, develop predictive models, and help drive data-driven decision-making across business functions. The role requires strong expertise in Python, SQL, machine learning algorithms, time-series forecasting, anomaly detection, and data storytelling. The candidate will work closely with business stakeholders, data engineers, product owners, and technology teams to solve critical operational and strategic challenges using data science methodologies. Experience with cloud and modern data platforms such as Databricks, Snowflake, Microsoft Fabric, and exposure to the C3 AI Platform will be highly preferred. Key Responsibilities: Data Science & Analytics Develop, implement, and maintain machine learning models for classification, regression, clustering, recommendation systems, and predictive analytics. Design and execute advanced statistical analyses to identify business trends, risks, and opportunities. Perform exploratory data analysis (EDA) to uncover patterns and generate actionable insights from structured and unstructured datasets. Build forecasting models using time-series techniques for business planning, demand forecasting, asset performance prediction, and operational optimization. Develop anomaly detection models to identify unusual patterns, operational failures, fraud indicators, or equipment performance issues. Conduct root-cause analysis and hypothesis testing to support business decision-making. Machine Learning Model Development Design and implement end-to-end machine learning pipelines from data ingestion to deployment. Perform feature engineering, feature selection, and data transformation to improve model performance. Evaluate models using appropriate validation techniques, performance metrics, and cross-validation methodologies. Optimize machine learning algorithms for scalability, accuracy, and interpretability. Monitor model performance and implement retraining strategies to ensure sustained effectiveness. Data Management & Engineering Collaboration Partner with data engineering teams to build scalable data pipelines and analytical data models. Work with large datasets using SQL, distributed computing frameworks, and cloud-based analytics platforms. Ensure data quality, consistency, and governance standards are maintained throughout the analytics lifecycle. Business Engagement & Communication Engage with business stakeholders to understand requirements, translate business problems into analytical solutions, and define success metrics. Present analytical findings, model results, and recommendations to both technical and non-technical audiences. Translate complex data science concepts into business-friendly insights and actionable recommendations. Support strategic initiatives by providing data-driven forecasting and scenario analysis. Visualization & Reporting Develop interactive dashboards and visualizations using Power BI, Tableau, or equivalent tools. Communicate model outcomes and business insights through compelling visual storytelling and executive presentations. Qualifications: MS or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, Operations Research, or a related quantitative field. 5+ years of applied machine learning, data science, or AI experience in a professional setting. Demonstrated experience owning projects or major workstreams from initial problem definition through delivery. Excellent programming skills in Python to include strong overall OOP experience. Strong proficiency with machine learning and data science tools such as Scikit-learn, PyTorch, TensorFlow, pandas, NumPy, XGBoost, or similar frameworks. Broad knowledge of machine learning and AI methods, including when to apply different approaches and what tradeoffs to consider. Project experience in several of the following areas: supervised learning, unsupervised learning, time series forecasting, deep learning, operations research, optimization, anomaly detection, or Generative AI. Familiarity with the machine learning lifecycle, including experimentation, versioning, deployment, monitoring, governance, and retraining. Experience with production-oriented ML tools or workflow platforms such as MLflow, Airflow, Kubeflow, Databricks, or similar. Familiarity with scalable data and AI technologies such as Spark, distributed processing, streaming systems, or cloud-based ML services. Prior exposure to AWS, Azure, or Google Cloud, especially AI/ML services, is advantageous. Ability to lead independently while collaborating effectively with client, product, engineering, and delivery teams. Strong communication skills, including the ability to explain complex analytical work clearly to business stakeholders. High ownership mindset, strong judgment, practical problem-solving ability, and a desire to create measurable business impact. Preferred Qualifications: Hands-on experience with the C3 AI platform . Experience working in an embedded client environment, partner delivery model, enterprise SaaS implementation, or AI platform delivery role. Experience delivering AI solutions for large enterprises or Fortune 500 clients. Domain experience in manufacturing, energy, utilities, supply chain, aerospace, telecommunications, financial services, or other operationally complex industries. Experience with demand forecasting, asset reliability planning, predictive maintenance, inventory optimization, or supply chain optimization. Experience mentoring junior team members or leading small technical teams. Pay: The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions, including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: $120,000 - $165,000. In addition, you may be eligible for a discretionary bonus for the current performance period. Benefits: As a full-time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plans in accordance with the plan documents, which may be amended from time to time. You will be eligible for benefits on the first day of employment with the Company. In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms. The Company provides for 11 paid holidays and 12 weeks of Parental Leave. We also follow a "free time" PTO policy, allowing you the flexibility to take the time needed for either sick time or vacation. Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

GovCIO LLC is seeking a Data Scientist to support federal digital modernization initiatives. You will design and deploy data pipelines, build predictive and prescriptive models, and turn complex federal datasets into actionable insights. Responsibilities include collaborating with engineers and product teams, applying statistical and machine learning techniques, developing dashboards and data visualizations, and ensuring data quality and governance. You'll work in a mission-driven, agile environment using modern cloud and analytics tools to improve government services and mission outcomes at national scale. Responsibilities Design, build, and maintain data pipelines and ETL workflows for federal datasets Develop and validate statistical and machine learning models to support mission outcomes Create dashboards and data visualizations to communicate insights to stakeholders Collaborate with engineers, product owners, and mission experts in an agile environment Ensure data quality, governance, and documentation of models and analytics solutions Evaluate new tools, techniques, and datasets to advance analytics capabilities Required Skills Python SQLMachine learning Statistical analysis Data visualization (Tableau/Power BI) Cloud platforms (AWS/Azure/GCP) ETL/data pipelines Big data tools (Spark/Hadoop) Version control (Git) Dashboard development

Lead analytics initiatives for the Digital Experience Insights team, developing predictive and statistical models, conducting quantitative research, and creating executive visualizations. Partner with Product, Engineering, and Business leaders to turn complex data findings into actionable strategy. This role is based primarily in Everpure's Santa Clara office. Responsibilities Develop machine-learning models for prediction, time-series forecasting, clustering, churn reduction, anomaly detection, and recommendations. Apply advanced statistical and computational methods to large datasets. Conduct quantitative research and experimental design. Create executive-level visual analytics and communicate complex findings. Partner with Product, Engineering, and Business leaders to translate analysis into strategy. Required Skills Python SQLPredictive modeling Time-series prediction Clustering Churn modeling Anomaly detection Recommendation systems Statistical modeling Experimental design

Job Family: Data Science Consulting Travel Required: None Clearance Required: Active Top Secret SCI with Polygraph What You Will Do : Our Data and Analytics consultants help clients maximize the value of their data. This high performing team works with clients to implement the full spectrum of data analytics and data science, from data querying and data wrangling to data visualization and dashboarding for business intelligence (BI), to predictive analytics, machine learning, and artificial intelligence. They help clients define their information strategy, architecture, and governance, get the most value from business intelligence and analytics, and implement enterprise content and data management solutions to enable business insights, reduce cost and complexity, increase trust and integrity, and improve operational effectiveness. The successful candidate will bring expertise in developing, building, and maintaining data assets and managing a team. This is a high visibility role and the candidate will be expected to speak confidently and intelligently about a variety of data products, methodologies, industry trends and challenges. This role will be involved in managing and maintaining client relationships as well as proactively participate in business development discussions. The candidate should demonstrate the flexibility to pivot and respond quickly to a dynamic and evolving company culture and broader energy transition landscape. Duties will include: Coordinating and leading internal team actions to meet project and client objectives. Consulting with the client to determine analytics required, technical solutions and methods to ensure a high confidence model for client decision making. Interfacing with Client Subject Matter Experts to design, develop, validate and deploy capabilities that enable client objectives. What You Will Need : An ACTIVE and MAINTAINED TS/SCI Federal or DoD security clearance with a FULL SCOPE (FS/FSP) polygraph Bachelor's degree THREE (3) or more years of experience Data Science or Data Analytics. Experience cleaning, manipulating, and pre-processing data using Python, SQL, R, or Tableau Prep Builder. Experience developing reports and dashboards for business intelligence, utilizing D ata Visualization tools such as Tableau Excellent communication skills, both verbal and written What Would Be Nice to Have : M.S./M.A. in Data Science/Analytics, Statistics, Mathematics, Operations Research, Computer Science, Information Systems, Engineering, Economics, or similar quantitative/computational discipline. Tableau Desktop Certification: Certified Professional, Certified Associate, Specialist. Tableau Server Certification: Certified Professional, Certified Associate. Proficiency querying data in SQL. Experience performing data science / analytics, such as statistical modelling, predictive analysis, or machine learning using Python or R. Experience with MS Forms and Power Automate. Ability to support clients in identifying and addressing needs, building relationships, and driving solutions forward and experience leading small teams. 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: Develop, implement, and validate statistical models and analytical methodologies to support client mission objectives Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies in large and complex datasets Design and deploy predictive and prescriptive models to enable data-driven decision-making Apply advanced analytics to Navy-specific domains such as logistics , maintenance, and operational readiness Collaborate with data engineers, developers, and stakeholders to operationalize models within production environments Translate business questions into analytical approaches and clearly communicate findings to technical and non-technical audiences Build and maintain reusable analytical frameworks, code libraries, and model pipelines Apply machine learning techniques to solve classification, regression, clustering, and optimization problems Develop dashboards and visualizations, including Qlik applications, to communicate insights and model outputs effectively Conduct model validation, tuning, and performance monitoring to ensure accuracy and reliability Document methodologies, assumptions, and results to support transparency and reproducibility What You Will Need: An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance. Bachelor's degree THREE (3) or more years of experience in data science, advanced analytics, or applied statistical modeling roles Experience in Python, R, and SQL for data analysis, modeling, and data manipulation Experience applying machine learning techniques and statistical methods to real-world datasets Experience working with large, complex datasets across logistics , maintenance, supply chain, or readiness domains Experience developing data visualizations and dashboards using Qlik or similar tools Experience working within cloud or big data environments such as Databricks or similar platforms Experience working in Agile or iterative development environments Experience supporting government or defense clients (Navy experience preferred) Ability to work onsite in a client environment as required What Would Be Nice To Have: Familiarity with deploying models or integrating analytics into operational workflows Strong foundation in statistics, mathematics, or quantitative analysis (e.g., regression, hypothesis testing, time series analysis) Statistical modeling and machine learning Ability to translate complex analytical outputs into actionable recommendations for stakeholders Experience working alongside or within data platforms (e.g., Palantir Foundry or similar environments) is a plus Data analysis and interpretation Python, R, SQL programming Data visualization (Qlik, Tableau, Power BI, etc.) Big data platforms (Databricks, Snowflake, AWS, Azure, Palantir Foundry, etc.) 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.

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