Pay Range: $50.00hr - $55.00hr Job Overview: As a Consulting Data Engineer, the successful candidate will architect, build, and optimize the next generation of real-time healthcare data platforms and event-driven architectures. The candidate will play a foundational role in moving clinical, operational, and financial data away from legacy batch processing toward high-throughput, near-zero-latency streaming pipelines. In this role, the candidate will champion modern data engineering practices, design highly scalable cloud-native pipelines, and mentor a growing team of engineers. The candidate will bridge the gap between complex electronic health records (EHR) and data consumers-enabling data scientists, software engineers, and clinical analysts to securely access, stream, and query compliant data at scale to improve patient outcomes and operational efficiency. Core Responsibilities: Architect Real-Time Pipelines: Design, implement, and monitor high-throughput, fault-tolerant streaming pipelines that ingest and process millions of concurrent healthcare data events (e.g., live telemetry, HL7 feeds, ADT messages). Scale Google Cloud Infrastructure: Build and maintain scalable, secure, and cost-effective cloud data infrastructure using Google Cloud healthcare-native tools and Infrastructure as Code (IaC). Enforce Healthcare Compliance & Security: Uphold strict data security protocols (HIPAA, HITRUST, SOC2) by building robust data lakehouse architectures that enforce PHI/PII masking, role-based access control (RBAC), and encryption at rest and in transit. Enable Self-Service Data & Interoperability: Build out streaming data ecosystems that support modern healthcare interoperability, managing real-time data catalogs and schema registries. Promote Code Excellence: Write modular, highly reusable, and performance-tested code; lead code reviews and establish standardized CI/CD automated deployment workflows. Optimize Data Reliability: Set and champion strict SLAs for clinical data delivery, establish automated data-quality testing, and implement proactive system monitoring and alerting. Collaborate & Mentor: Work closely with Data Architects, Clinical Product Managers, and AI/ML teams to translate healthcare requirements into technical blueprints while mentoring mid-level engineers. Required Qualifications: 13+ years of experience in dedicated data engineering, data architecture, or distributed systems software engineering roles. 4+ years of experience specifically within the healthcare domain (payer, provider, digital health, or health tech). Google Cloud Certified Professional Data Engineer (or equivalent proven expert-level architecture experience on GCP). Advanced Event-Driven Architecture: Mastery of high-volume streaming technologies including Apache Kafka and Google Cloud Pub/Sub for decoupled, real-time message routing. Stream Processing: Deep hands-on experience with Apache Flink or Google Cloud Dataflow (Apache Beam) for real-time streaming, complex event processing (CEP), windowing, and streaming data transformations. Interoperability Standards: Deep expertise working with FHIR (Fast Healthcare Interoperability Resources) JSON structures, HL7 v2/v3 messaging, and DICOM imaging standard streams. GCP Healthcare Tools: Hands-on experience implementing and scaling the Google Cloud Healthcare API (specifically FHIR stores and HL7v2 stores). EHR Integration: Experience integrating streaming pipelines with major EHR systems (such as Epic, Cerner, or Meditech). Google Cloud Ecosystem: Technical mastery of BigQuery (including partitioning, clustering, and streaming inserts), Cloud Storage, Dataproc, and Cloud Composer (Apache Airflow). Programming Languages: Proficiency in Python, Scala, or Java, with a strong focus on writing optimized code for distributed computing platforms (like Spark or Beam). Modern Data Stack & Modeling: Mastery of modern analytics engineering frameworks (such as dbt), dimensional data modeling, and lakehouse architectures (e.g., Iceberg, Delta Lake). DevOps & Automation: Robust experience building automated CI/CD pipelines (GitHub Actions, GitLab CI) and managing infrastructure using Terraform. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
11/14/2026
Full time
Pay Range: $50.00hr - $55.00hr Job Overview: As a Consulting Data Engineer, the successful candidate will architect, build, and optimize the next generation of real-time healthcare data platforms and event-driven architectures. The candidate will play a foundational role in moving clinical, operational, and financial data away from legacy batch processing toward high-throughput, near-zero-latency streaming pipelines. In this role, the candidate will champion modern data engineering practices, design highly scalable cloud-native pipelines, and mentor a growing team of engineers. The candidate will bridge the gap between complex electronic health records (EHR) and data consumers-enabling data scientists, software engineers, and clinical analysts to securely access, stream, and query compliant data at scale to improve patient outcomes and operational efficiency. Core Responsibilities: Architect Real-Time Pipelines: Design, implement, and monitor high-throughput, fault-tolerant streaming pipelines that ingest and process millions of concurrent healthcare data events (e.g., live telemetry, HL7 feeds, ADT messages). Scale Google Cloud Infrastructure: Build and maintain scalable, secure, and cost-effective cloud data infrastructure using Google Cloud healthcare-native tools and Infrastructure as Code (IaC). Enforce Healthcare Compliance & Security: Uphold strict data security protocols (HIPAA, HITRUST, SOC2) by building robust data lakehouse architectures that enforce PHI/PII masking, role-based access control (RBAC), and encryption at rest and in transit. Enable Self-Service Data & Interoperability: Build out streaming data ecosystems that support modern healthcare interoperability, managing real-time data catalogs and schema registries. Promote Code Excellence: Write modular, highly reusable, and performance-tested code; lead code reviews and establish standardized CI/CD automated deployment workflows. Optimize Data Reliability: Set and champion strict SLAs for clinical data delivery, establish automated data-quality testing, and implement proactive system monitoring and alerting. Collaborate & Mentor: Work closely with Data Architects, Clinical Product Managers, and AI/ML teams to translate healthcare requirements into technical blueprints while mentoring mid-level engineers. Required Qualifications: 13+ years of experience in dedicated data engineering, data architecture, or distributed systems software engineering roles. 4+ years of experience specifically within the healthcare domain (payer, provider, digital health, or health tech). Google Cloud Certified Professional Data Engineer (or equivalent proven expert-level architecture experience on GCP). Advanced Event-Driven Architecture: Mastery of high-volume streaming technologies including Apache Kafka and Google Cloud Pub/Sub for decoupled, real-time message routing. Stream Processing: Deep hands-on experience with Apache Flink or Google Cloud Dataflow (Apache Beam) for real-time streaming, complex event processing (CEP), windowing, and streaming data transformations. Interoperability Standards: Deep expertise working with FHIR (Fast Healthcare Interoperability Resources) JSON structures, HL7 v2/v3 messaging, and DICOM imaging standard streams. GCP Healthcare Tools: Hands-on experience implementing and scaling the Google Cloud Healthcare API (specifically FHIR stores and HL7v2 stores). EHR Integration: Experience integrating streaming pipelines with major EHR systems (such as Epic, Cerner, or Meditech). Google Cloud Ecosystem: Technical mastery of BigQuery (including partitioning, clustering, and streaming inserts), Cloud Storage, Dataproc, and Cloud Composer (Apache Airflow). Programming Languages: Proficiency in Python, Scala, or Java, with a strong focus on writing optimized code for distributed computing platforms (like Spark or Beam). Modern Data Stack & Modeling: Mastery of modern analytics engineering frameworks (such as dbt), dimensional data modeling, and lakehouse architectures (e.g., Iceberg, Delta Lake). DevOps & Automation: Robust experience building automated CI/CD pipelines (GitHub Actions, GitLab CI) and managing infrastructure using Terraform. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
Pay Range: $50.00hr - $55.00hr Job Overview: As a Consulting Data Engineer, the successful candidate will architect, build, and optimize the next generation of real-time healthcare data platforms and event-driven architectures. The candidate will play a foundational role in moving clinical, operational, and financial data away from legacy batch processing toward high-throughput, near-zero-latency streaming pipelines. In this role, the candidate will champion modern data engineering practices, design highly scalable cloud-native pipelines, and mentor a growing team of engineers. The candidate will bridge the gap between complex electronic health records (EHR) and data consumers-enabling data scientists, software engineers, and clinical analysts to securely access, stream, and query compliant data at scale to improve patient outcomes and operational efficiency. Core Responsibilities: Architect Real-Time Pipelines: Design, implement, and monitor high-throughput, fault-tolerant streaming pipelines that ingest and process millions of concurrent healthcare data events (e.g., live telemetry, HL7 feeds, ADT messages). Scale Google Cloud Infrastructure: Build and maintain scalable, secure, and cost-effective cloud data infrastructure using Google Cloud healthcare-native tools and Infrastructure as Code (IaC). Enforce Healthcare Compliance & Security: Uphold strict data security protocols (HIPAA, HITRUST, SOC2) by building robust data lakehouse architectures that enforce PHI/PII masking, role-based access control (RBAC), and encryption at rest and in transit. Enable Self-Service Data & Interoperability: Build out streaming data ecosystems that support modern healthcare interoperability, managing real-time data catalogs and schema registries. Promote Code Excellence: Write modular, highly reusable, and performance-tested code; lead code reviews and establish standardized CI/CD automated deployment workflows. Optimize Data Reliability: Set and champion strict SLAs for clinical data delivery, establish automated data-quality testing, and implement proactive system monitoring and alerting. Collaborate & Mentor: Work closely with Data Architects, Clinical Product Managers, and AI/ML teams to translate healthcare requirements into technical blueprints while mentoring mid-level engineers. Required Qualifications: 13+ years of experience in dedicated data engineering, data architecture, or distributed systems software engineering roles. 4+ years of experience specifically within the healthcare domain (payer, provider, digital health, or health tech). Google Cloud Certified Professional Data Engineer (or equivalent proven expert-level architecture experience on GCP). Advanced Event-Driven Architecture: Mastery of high-volume streaming technologies including Apache Kafka and Google Cloud Pub/Sub for decoupled, real-time message routing. Stream Processing: Deep hands-on experience with Apache Flink or Google Cloud Dataflow (Apache Beam) for real-time streaming, complex event processing (CEP), windowing, and streaming data transformations. Interoperability Standards: Deep expertise working with FHIR (Fast Healthcare Interoperability Resources) JSON structures, HL7 v2/v3 messaging, and DICOM imaging standard streams. GCP Healthcare Tools: Hands-on experience implementing and scaling the Google Cloud Healthcare API (specifically FHIR stores and HL7v2 stores). EHR Integration: Experience integrating streaming pipelines with major EHR systems (such as Epic, Cerner, or Meditech). Google Cloud Ecosystem: Technical mastery of BigQuery (including partitioning, clustering, and streaming inserts), Cloud Storage, Dataproc, and Cloud Composer (Apache Airflow). Programming Languages: Proficiency in Python, Scala, or Java, with a strong focus on writing optimized code for distributed computing platforms (like Spark or Beam). Modern Data Stack & Modeling: Mastery of modern analytics engineering frameworks (such as dbt), dimensional data modeling, and lakehouse architectures (e.g., Iceberg, Delta Lake). DevOps & Automation: Robust experience building automated CI/CD pipelines (GitHub Actions, GitLab CI) and managing infrastructure using Terraform. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
11/14/2026
Full time
Pay Range: $50.00hr - $55.00hr Job Overview: As a Consulting Data Engineer, the successful candidate will architect, build, and optimize the next generation of real-time healthcare data platforms and event-driven architectures. The candidate will play a foundational role in moving clinical, operational, and financial data away from legacy batch processing toward high-throughput, near-zero-latency streaming pipelines. In this role, the candidate will champion modern data engineering practices, design highly scalable cloud-native pipelines, and mentor a growing team of engineers. The candidate will bridge the gap between complex electronic health records (EHR) and data consumers-enabling data scientists, software engineers, and clinical analysts to securely access, stream, and query compliant data at scale to improve patient outcomes and operational efficiency. Core Responsibilities: Architect Real-Time Pipelines: Design, implement, and monitor high-throughput, fault-tolerant streaming pipelines that ingest and process millions of concurrent healthcare data events (e.g., live telemetry, HL7 feeds, ADT messages). Scale Google Cloud Infrastructure: Build and maintain scalable, secure, and cost-effective cloud data infrastructure using Google Cloud healthcare-native tools and Infrastructure as Code (IaC). Enforce Healthcare Compliance & Security: Uphold strict data security protocols (HIPAA, HITRUST, SOC2) by building robust data lakehouse architectures that enforce PHI/PII masking, role-based access control (RBAC), and encryption at rest and in transit. Enable Self-Service Data & Interoperability: Build out streaming data ecosystems that support modern healthcare interoperability, managing real-time data catalogs and schema registries. Promote Code Excellence: Write modular, highly reusable, and performance-tested code; lead code reviews and establish standardized CI/CD automated deployment workflows. Optimize Data Reliability: Set and champion strict SLAs for clinical data delivery, establish automated data-quality testing, and implement proactive system monitoring and alerting. Collaborate & Mentor: Work closely with Data Architects, Clinical Product Managers, and AI/ML teams to translate healthcare requirements into technical blueprints while mentoring mid-level engineers. Required Qualifications: 13+ years of experience in dedicated data engineering, data architecture, or distributed systems software engineering roles. 4+ years of experience specifically within the healthcare domain (payer, provider, digital health, or health tech). Google Cloud Certified Professional Data Engineer (or equivalent proven expert-level architecture experience on GCP). Advanced Event-Driven Architecture: Mastery of high-volume streaming technologies including Apache Kafka and Google Cloud Pub/Sub for decoupled, real-time message routing. Stream Processing: Deep hands-on experience with Apache Flink or Google Cloud Dataflow (Apache Beam) for real-time streaming, complex event processing (CEP), windowing, and streaming data transformations. Interoperability Standards: Deep expertise working with FHIR (Fast Healthcare Interoperability Resources) JSON structures, HL7 v2/v3 messaging, and DICOM imaging standard streams. GCP Healthcare Tools: Hands-on experience implementing and scaling the Google Cloud Healthcare API (specifically FHIR stores and HL7v2 stores). EHR Integration: Experience integrating streaming pipelines with major EHR systems (such as Epic, Cerner, or Meditech). Google Cloud Ecosystem: Technical mastery of BigQuery (including partitioning, clustering, and streaming inserts), Cloud Storage, Dataproc, and Cloud Composer (Apache Airflow). Programming Languages: Proficiency in Python, Scala, or Java, with a strong focus on writing optimized code for distributed computing platforms (like Spark or Beam). Modern Data Stack & Modeling: Mastery of modern analytics engineering frameworks (such as dbt), dimensional data modeling, and lakehouse architectures (e.g., Iceberg, Delta Lake). DevOps & Automation: Robust experience building automated CI/CD pipelines (GitHub Actions, GitLab CI) and managing infrastructure using Terraform. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
This job is with WTW, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Description Employment-based non-immigrant visa sponsorship and/or assistance is not offered for this specific job opportunity. We will only consider candidates who are currently authorized to work in the United States and who will not require sponsorship now or in the future. Please note: student visas, CPT, OPT, H-1B, TN, and other temporary work authorizations are considered restricted forms of employment eligibility. Once these expire, the candidate must be able to present another valid form of work authorization. Start Date: August 2 nd , 2027 Hybrid Locations: New York Graduate Program Overview The CRB Graduate Development Program (GDP) is a non-rotational 17-month program that provides the opportunity to develop a broad knowledge base, varied skills, and diverse network. This program is designed to set you up with a holistic view of CRB with hands-on experience, insight, and opportunities to make an impact and shape your own career. GDP participants will be immersed in a 1-week orientation followed by a robust onboarding training learning about various functions within CRB. Our program is designed to provide graduates with a well-rounded understanding of the industry while having the opportunity to deep dive within their respective business area. R&A Enterprise Risk Consulting Overview Colleagues working in Risk & Analytics' Enterprise Risk Consulting (ERC) team provide our clients with a smarter way to analyze risk, using quantification, structured approaches, risk analytics tools and subject matter expertise to improve client outcomes. With our expertise and tailored solutions, we improve complex enterprise risk management by identifying, quantifying and mitigating unpredictable, interconnected risks. We currently work with some of the world's largest and complex organizations to assess and manage their strategic risks. We also work with smaller organizations early in their ERM journeys. We work across many industries including Food & Beverage, Professional Services, Transportation / Logistics, Energy, Construction, Manufacturing and others. Work within ERC is predominantly project-based, and you will often be involved in multiple projects simultaneously. Our work is often collaborative, providing exposure to a range of teams within the division. Responsibilities: As an Analyst within Risk & Analytics' Enterprise Risk Consulting (ERC) team, you will support the delivery of client projects that help organizations identify, assess, quantify, and manage enterprise risks while strengthening organizational resilience. You will work alongside consultants, data scientists, actuaries, catastrophe modelers, business continuity specialists, and industry experts to deliver solutions for some of the world's largest organizations. Project work may include: Enterprise Risk Management (ERM) assessments and maturity reviews Enterprise-wide risk identification, prioritization, and risk register development Risk appetite, tolerance, and governance framework design Strategic risk quantification and decision-support modeling Business Continuity Planning (BCP) and operational resilience programs Development of risk monitoring, reporting, and key risk indicators Benchmarking, research, and analysis to support client recommendations In this role, you will frequently collaborate with colleagues across WTW, including risk consulting, catastrophe modeling, climate, actuarial, insurance, and analytics teams to address complex client challenges. You will also contribute to the development of new consulting methodologies, tools, and thought leadership. As part of our innovation agenda, you will help explore and apply emerging AI-enabled approaches that enhance analytical insights, improve delivery efficiency, and create better outcomes for our clients. What You'll Gain Exposure to a wide variety of industries and risk challenges Experience working directly with senior client stakeholders Opportunities to develop analytical, consulting, and project management skills Collaboration with multidisciplinary teams across WTW Hands-on experience with innovative risk analytics and AI-enabled solutions A strong foundation for a career in enterprise risk management, business continuity, resilience, and risk consulting Compensation and Benefits Base salary range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that base salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, qualifications/experience, performance in the role and potential for revenue generation (Producer roles only). Qualifications Education and Qualifications: Bachelor's degree with a minimum of 3.0 GPA Date of Graduation between May 2026 - May 2027 Preferred Majors: Risk Management, Business, Finance, Economics, Accounting, Liberal Arts Intermediate to advance Excel skills Proficient in Microsoft Office Suite Competencies: Strong analytical, problem-solving, and critical thinking skills Excellent written and verbal communication skills, including the ability to translate complex concepts into clear, actionable insights Strong interpersonal and relationship-building skills, with the ability to collaborate effectively with colleagues, clients, and subject matter experts across functions Intellectual curiosity and a willingness to learn new methodologies, technologies, and AI-enabled approaches to consulting Strong organizational and project management skills with the ability to manage multiple priorities and deadlines Self-starter mindset with the ability to work independently while contributing to team success Proficiency in Microsoft Excel, PowerPoint, and Word Interest in enterprise risk management, business continuity, resilience, analytics, and organizational decision-making Compensation and Benefits Base salary range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, qualifications/experience, performance in the role and potential for revenue generation (Producer roles only). Compensation The hourly rate being offered for this role is $36.00hr - $39.00hr USD. This role is also eligible for overtime. Company Benefits: WTW provides a competitive benefit package which includes the following (eligibility requirements apply): Health and Welfare Benefits: Medical (including prescription coverage), Dental, Vision, Health Savings Account, Commuter Account, Health Care and Dependent Care Flexible Spending Accounts, Group Accident, Group Critical Illness, Life Insurance, AD&D, Group Legal, Identify Theft Protection, Wellbeing Program and Work/Life Resources (including Employee Assistance Program) Leave Benefits: Paid Holidays, Annual Paid Time Off (includes paid state/local paid leave where required), Short-Term Disability, Long-Term Disability, Other Leaves (e.g., Bereavement, FMLA, ADA, Jury Duty, Military Leave, and Parental and Adoption Leave), Paid Time Off Retirement Benefits: Contributory Pension Plan and Savings Plan (401k) Future Career Opportunities: Our internship program serves as a key talent pipeline for future full-time Graduate opportunities. As a result, candidates must meet the graduation date requirements specified in the posting. If a candidate's expected graduation date changes after applying, they are expected to promptly inform their recruiter or manager, as this may impact eligibility for current or future opportunities. Recruiting tips: WTW specializes in preparing for the unknown. Here's how to get ready for the big day: Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles County Fair Chance Ordinance for Employers, we will consider for employment qualified applicants with arrest and conviction records This position will remain posted for a minimum of three business days from the date posted or until sufficient/appropriate candidate slate has been identified. EOE, including disability/vets
11/14/2026
Full time
This job is with WTW, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Description Employment-based non-immigrant visa sponsorship and/or assistance is not offered for this specific job opportunity. We will only consider candidates who are currently authorized to work in the United States and who will not require sponsorship now or in the future. Please note: student visas, CPT, OPT, H-1B, TN, and other temporary work authorizations are considered restricted forms of employment eligibility. Once these expire, the candidate must be able to present another valid form of work authorization. Start Date: August 2 nd , 2027 Hybrid Locations: New York Graduate Program Overview The CRB Graduate Development Program (GDP) is a non-rotational 17-month program that provides the opportunity to develop a broad knowledge base, varied skills, and diverse network. This program is designed to set you up with a holistic view of CRB with hands-on experience, insight, and opportunities to make an impact and shape your own career. GDP participants will be immersed in a 1-week orientation followed by a robust onboarding training learning about various functions within CRB. Our program is designed to provide graduates with a well-rounded understanding of the industry while having the opportunity to deep dive within their respective business area. R&A Enterprise Risk Consulting Overview Colleagues working in Risk & Analytics' Enterprise Risk Consulting (ERC) team provide our clients with a smarter way to analyze risk, using quantification, structured approaches, risk analytics tools and subject matter expertise to improve client outcomes. With our expertise and tailored solutions, we improve complex enterprise risk management by identifying, quantifying and mitigating unpredictable, interconnected risks. We currently work with some of the world's largest and complex organizations to assess and manage their strategic risks. We also work with smaller organizations early in their ERM journeys. We work across many industries including Food & Beverage, Professional Services, Transportation / Logistics, Energy, Construction, Manufacturing and others. Work within ERC is predominantly project-based, and you will often be involved in multiple projects simultaneously. Our work is often collaborative, providing exposure to a range of teams within the division. Responsibilities: As an Analyst within Risk & Analytics' Enterprise Risk Consulting (ERC) team, you will support the delivery of client projects that help organizations identify, assess, quantify, and manage enterprise risks while strengthening organizational resilience. You will work alongside consultants, data scientists, actuaries, catastrophe modelers, business continuity specialists, and industry experts to deliver solutions for some of the world's largest organizations. Project work may include: Enterprise Risk Management (ERM) assessments and maturity reviews Enterprise-wide risk identification, prioritization, and risk register development Risk appetite, tolerance, and governance framework design Strategic risk quantification and decision-support modeling Business Continuity Planning (BCP) and operational resilience programs Development of risk monitoring, reporting, and key risk indicators Benchmarking, research, and analysis to support client recommendations In this role, you will frequently collaborate with colleagues across WTW, including risk consulting, catastrophe modeling, climate, actuarial, insurance, and analytics teams to address complex client challenges. You will also contribute to the development of new consulting methodologies, tools, and thought leadership. As part of our innovation agenda, you will help explore and apply emerging AI-enabled approaches that enhance analytical insights, improve delivery efficiency, and create better outcomes for our clients. What You'll Gain Exposure to a wide variety of industries and risk challenges Experience working directly with senior client stakeholders Opportunities to develop analytical, consulting, and project management skills Collaboration with multidisciplinary teams across WTW Hands-on experience with innovative risk analytics and AI-enabled solutions A strong foundation for a career in enterprise risk management, business continuity, resilience, and risk consulting Compensation and Benefits Base salary range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that base salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, qualifications/experience, performance in the role and potential for revenue generation (Producer roles only). Qualifications Education and Qualifications: Bachelor's degree with a minimum of 3.0 GPA Date of Graduation between May 2026 - May 2027 Preferred Majors: Risk Management, Business, Finance, Economics, Accounting, Liberal Arts Intermediate to advance Excel skills Proficient in Microsoft Office Suite Competencies: Strong analytical, problem-solving, and critical thinking skills Excellent written and verbal communication skills, including the ability to translate complex concepts into clear, actionable insights Strong interpersonal and relationship-building skills, with the ability to collaborate effectively with colleagues, clients, and subject matter experts across functions Intellectual curiosity and a willingness to learn new methodologies, technologies, and AI-enabled approaches to consulting Strong organizational and project management skills with the ability to manage multiple priorities and deadlines Self-starter mindset with the ability to work independently while contributing to team success Proficiency in Microsoft Excel, PowerPoint, and Word Interest in enterprise risk management, business continuity, resilience, analytics, and organizational decision-making Compensation and Benefits Base salary range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, qualifications/experience, performance in the role and potential for revenue generation (Producer roles only). Compensation The hourly rate being offered for this role is $36.00hr - $39.00hr USD. This role is also eligible for overtime. Company Benefits: WTW provides a competitive benefit package which includes the following (eligibility requirements apply): Health and Welfare Benefits: Medical (including prescription coverage), Dental, Vision, Health Savings Account, Commuter Account, Health Care and Dependent Care Flexible Spending Accounts, Group Accident, Group Critical Illness, Life Insurance, AD&D, Group Legal, Identify Theft Protection, Wellbeing Program and Work/Life Resources (including Employee Assistance Program) Leave Benefits: Paid Holidays, Annual Paid Time Off (includes paid state/local paid leave where required), Short-Term Disability, Long-Term Disability, Other Leaves (e.g., Bereavement, FMLA, ADA, Jury Duty, Military Leave, and Parental and Adoption Leave), Paid Time Off Retirement Benefits: Contributory Pension Plan and Savings Plan (401k) Future Career Opportunities: Our internship program serves as a key talent pipeline for future full-time Graduate opportunities. As a result, candidates must meet the graduation date requirements specified in the posting. If a candidate's expected graduation date changes after applying, they are expected to promptly inform their recruiter or manager, as this may impact eligibility for current or future opportunities. Recruiting tips: WTW specializes in preparing for the unknown. Here's how to get ready for the big day: Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles County Fair Chance Ordinance for Employers, we will consider for employment qualified applicants with arrest and conviction records This position will remain posted for a minimum of three business days from the date posted or until sufficient/appropriate candidate slate has been identified. EOE, including disability/vets
Starbucks is seeking a Senior/Lead Decision Scientist to shape data-driven strategy across its global coffeehouse business. In this role, you will partner with Retail, Supply Chain, and Marketing teams to design experiments, build predictive and optimization models, and translate complex data into clear, actionable insights. You will lead advanced analytics projects, define key metrics, and develop dashboards that guide pricing, assortment, and customer experience decisions. You will mentor other analysts, champion best practices in experimentation and data ethics, and help embed a culture of evidence-based decision making across Starbucks. Responsibilities Lead design and analysis of experiments to optimize pricing, promotions, and customer experience Build and deploy predictive and optimization models to support retail and supply chain decisions Develop dashboards and self-serve analytics tools for stakeholders Define and refine key performance metrics and measurement frameworks Translate complex analytical findings into clear, actionable business recommendations Partner with cross-functional teams in Marketing, Operations, and Supply Chain Mentor and guide junior analysts and decision scientists Promote best practices in data quality, experimentation, and analytics governance Required Skills Statistical modeling A/B testing and experimentation design Machine learning SQLPython or RData visualization (Tableau/Power BI) Predictive analytics Optimization and forecasting Big data tools (e.g., Spark, Hive) Business intelligence and dashboarding
11/01/2026
Full time
Starbucks is seeking a Senior/Lead Decision Scientist to shape data-driven strategy across its global coffeehouse business. In this role, you will partner with Retail, Supply Chain, and Marketing teams to design experiments, build predictive and optimization models, and translate complex data into clear, actionable insights. You will lead advanced analytics projects, define key metrics, and develop dashboards that guide pricing, assortment, and customer experience decisions. You will mentor other analysts, champion best practices in experimentation and data ethics, and help embed a culture of evidence-based decision making across Starbucks. Responsibilities Lead design and analysis of experiments to optimize pricing, promotions, and customer experience Build and deploy predictive and optimization models to support retail and supply chain decisions Develop dashboards and self-serve analytics tools for stakeholders Define and refine key performance metrics and measurement frameworks Translate complex analytical findings into clear, actionable business recommendations Partner with cross-functional teams in Marketing, Operations, and Supply Chain Mentor and guide junior analysts and decision scientists Promote best practices in data quality, experimentation, and analytics governance Required Skills Statistical modeling A/B testing and experimentation design Machine learning SQLPython or RData visualization (Tableau/Power BI) Predictive analytics Optimization and forecasting Big data tools (e.g., Spark, Hive) Business intelligence and dashboarding
Starbucks is seeking a Senior/Lead Decision Scientist to drive data-informed strategy across our global coffeehouse business. In this role, you'll translate complex data into clear insights that improve customer experience, store operations, and digital engagement. You'll design experiments, develop predictive and prescriptive models, and build dashboards that guide leaders in merchandising, pricing, and loyalty initiatives. Partnering with cross-functional teams, you'll define metrics, validate hypotheses, and tell compelling data stories. You'll mentor junior analysts, champion data quality and governance, and help shape a culture of evidence-based, ethical decision-making at scale. Responsibilities Lead design and execution of experiments and A/B tests to optimize customer experience, pricing, and promotions. Develop predictive and prescriptive models to support demand forecasting, personalization, and store operations. Translate complex data into clear, actionable insights and narratives for business and executive stakeholders. Build and maintain dashboards, reports, and self-service analytics tools for cross-functional teams. Define and refine key performance metrics for digital, retail, and loyalty initiatives. Collaborate with product, marketing, operations, and finance to identify and prioritize analytics opportunities. Ensure data quality, governance, and proper use of data across projects. Mentor and guide junior analysts and data scientists on best practices and frameworks. Evaluate and implement new analytical methods, tools, and data sources to enhance decision-making. Champion a culture of ethical, evidence-based decision-making aligned with Starbucks values. Required Skills Data science Statistical analysis A/B testing and experimentation Predictive modeling Machine learning SQLPython or RData visualization (Tableau/Power BI) Data storytelling and communication Business intelligence and reporting
11/01/2026
Full time
Starbucks is seeking a Senior/Lead Decision Scientist to drive data-informed strategy across our global coffeehouse business. In this role, you'll translate complex data into clear insights that improve customer experience, store operations, and digital engagement. You'll design experiments, develop predictive and prescriptive models, and build dashboards that guide leaders in merchandising, pricing, and loyalty initiatives. Partnering with cross-functional teams, you'll define metrics, validate hypotheses, and tell compelling data stories. You'll mentor junior analysts, champion data quality and governance, and help shape a culture of evidence-based, ethical decision-making at scale. Responsibilities Lead design and execution of experiments and A/B tests to optimize customer experience, pricing, and promotions. Develop predictive and prescriptive models to support demand forecasting, personalization, and store operations. Translate complex data into clear, actionable insights and narratives for business and executive stakeholders. Build and maintain dashboards, reports, and self-service analytics tools for cross-functional teams. Define and refine key performance metrics for digital, retail, and loyalty initiatives. Collaborate with product, marketing, operations, and finance to identify and prioritize analytics opportunities. Ensure data quality, governance, and proper use of data across projects. Mentor and guide junior analysts and data scientists on best practices and frameworks. Evaluate and implement new analytical methods, tools, and data sources to enhance decision-making. Champion a culture of ethical, evidence-based decision-making aligned with Starbucks values. Required Skills Data science Statistical analysis A/B testing and experimentation Predictive modeling Machine learning SQLPython or RData visualization (Tableau/Power BI) Data storytelling and communication Business intelligence and reporting
Starbucks is seeking a Senior/Lead Decision Scientist to drive data-informed strategy across our global coffee and food operations. In this role, you will use advanced analytics, experimentation, and predictive modeling to optimize pricing, product mix, and store performance. You'll partner with operations, marketing, and digital teams to translate complex data into clear insights, dashboards, and recommendations that enhance guest experience and profitability. You will mentor junior analysts, promote data literacy, and help shape a culture of ethical, responsible data use aligned with Starbucks' community and sustainability values. Responsibilities Develop and deploy advanced analytics, forecasting, and predictive models to inform pricing, product, and operational decisions. Design and analyze A/B tests and experiments to evaluate initiatives across stores and digital channels. Build clear dashboards and self-service BI tools for stakeholders in operations, marketing, and digital. Translate complex data into actionable insights and strategic recommendations for senior leaders. Partner with cross-functional teams to define metrics, KPIs, and measurement frameworks. Mentor and guide junior analysts and data scientists, promoting best practices in analytics and coding. Ensure data quality, governance, and ethical use of customer and operational data. Communicate findings through compelling presentations, visualizations, and written summaries. Collaborate with technology teams to improve data pipelines, tooling, and analytics platforms. Support long-term analytics roadmap aligned with Starbucks' sustainability, community, and growth goals. Required Skills SQLPython or RStatistical modeling Predictive analytics A/B testing and experimentation Machine learning fundamentals Data visualization (e.g., Tableau, Power BI) Big data tools (e.g., Spark, Hive) Dashboarding and reporting Business intelligence in retail/hospitality Data storytelling Forecasting and time-series analysis
11/01/2026
Full time
Starbucks is seeking a Senior/Lead Decision Scientist to drive data-informed strategy across our global coffee and food operations. In this role, you will use advanced analytics, experimentation, and predictive modeling to optimize pricing, product mix, and store performance. You'll partner with operations, marketing, and digital teams to translate complex data into clear insights, dashboards, and recommendations that enhance guest experience and profitability. You will mentor junior analysts, promote data literacy, and help shape a culture of ethical, responsible data use aligned with Starbucks' community and sustainability values. Responsibilities Develop and deploy advanced analytics, forecasting, and predictive models to inform pricing, product, and operational decisions. Design and analyze A/B tests and experiments to evaluate initiatives across stores and digital channels. Build clear dashboards and self-service BI tools for stakeholders in operations, marketing, and digital. Translate complex data into actionable insights and strategic recommendations for senior leaders. Partner with cross-functional teams to define metrics, KPIs, and measurement frameworks. Mentor and guide junior analysts and data scientists, promoting best practices in analytics and coding. Ensure data quality, governance, and ethical use of customer and operational data. Communicate findings through compelling presentations, visualizations, and written summaries. Collaborate with technology teams to improve data pipelines, tooling, and analytics platforms. Support long-term analytics roadmap aligned with Starbucks' sustainability, community, and growth goals. Required Skills SQLPython or RStatistical modeling Predictive analytics A/B testing and experimentation Machine learning fundamentals Data visualization (e.g., Tableau, Power BI) Big data tools (e.g., Spark, Hive) Dashboarding and reporting Business intelligence in retail/hospitality Data storytelling Forecasting and time-series analysis
Avanos Medical seeks an Associate Director IT Global Data Analytics, Innovation & Digital Experimentation to lead data strategy across our global medtech business. In this role, you will define and deliver advanced analytics, AI/ML, and data engineering solutions that optimize clinical, commercial, and operational decisions. You will own the data experimentation roadmap, partner with business and clinical leaders to identify high value use cases, and oversee end to end project delivery. Responsibilities include managing a technical team, governing data platforms, ensuring data quality, and championing innovation while maintaining security, privacy, and regulatory compliance in a patient-focused environment. Responsibilities Lead global data analytics and digital experimentation strategy for Avanos Medical Identify, prioritize, and deliver high-value analytics and AI/ML use cases across business functions Oversee design and implementation of data platforms, pipelines, and governance frameworks Manage and mentor a technical team of data engineers, scientists, and analysts Ensure data quality, integrity, security, and regulatory compliance in a healthcare context Partner with clinical, commercial, and operations leaders to translate needs into technical solutions Drive experimentation frameworks (A/B testing, pilots, POCs) to validate data-driven initiatives Report performance, insights, and ROI of analytics programs to senior leadership Collaborate with IT and cybersecurity to maintain resilient, scalable data infrastructure Champion a culture of innovation, continuous improvement, and patient-focused decision-making Required Skills Data analytics strategy Data engineering (ETL/ELT, data pipelines) Cloud data platforms (AWS, Azure, or GCP) SQL and relational databases Python or R for analytics and data science Machine learning and AI concepts BI and data visualization tools (Tableau, Power BI, etc.) A/B testing and experimentation frameworks Data governance, security, and privacy (including healthcare context) Project and stakeholder management Statistical analysis and modeling Data architecture and warehousing
11/01/2026
Full time
Avanos Medical seeks an Associate Director IT Global Data Analytics, Innovation & Digital Experimentation to lead data strategy across our global medtech business. In this role, you will define and deliver advanced analytics, AI/ML, and data engineering solutions that optimize clinical, commercial, and operational decisions. You will own the data experimentation roadmap, partner with business and clinical leaders to identify high value use cases, and oversee end to end project delivery. Responsibilities include managing a technical team, governing data platforms, ensuring data quality, and championing innovation while maintaining security, privacy, and regulatory compliance in a patient-focused environment. Responsibilities Lead global data analytics and digital experimentation strategy for Avanos Medical Identify, prioritize, and deliver high-value analytics and AI/ML use cases across business functions Oversee design and implementation of data platforms, pipelines, and governance frameworks Manage and mentor a technical team of data engineers, scientists, and analysts Ensure data quality, integrity, security, and regulatory compliance in a healthcare context Partner with clinical, commercial, and operations leaders to translate needs into technical solutions Drive experimentation frameworks (A/B testing, pilots, POCs) to validate data-driven initiatives Report performance, insights, and ROI of analytics programs to senior leadership Collaborate with IT and cybersecurity to maintain resilient, scalable data infrastructure Champion a culture of innovation, continuous improvement, and patient-focused decision-making Required Skills Data analytics strategy Data engineering (ETL/ELT, data pipelines) Cloud data platforms (AWS, Azure, or GCP) SQL and relational databases Python or R for analytics and data science Machine learning and AI concepts BI and data visualization tools (Tableau, Power BI, etc.) A/B testing and experimentation frameworks Data governance, security, and privacy (including healthcare context) Project and stakeholder management Statistical analysis and modeling Data architecture and warehousing
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
