Lead Data Scientist - Clinical Informatics

Role Description

CVS Health's Analytics & Behavior Change (A&BC) team is an organization working to solve some of the most challenging problems at the intersection of technology and healthcare. A&BC leverages advanced analytics, clinical informatics, and hypothesis-driven approaches to transform data into actionable, customer-centric insights that drive growth, improve health outcomes, and expand access to healthcare across all CVS Health businesses. Our teams build next-generation data and AI products that help power CVS Health to make healthier happen for 100+ million customers.

The A&BC organization is looking to grow its Clinical Data Science & AI team. Join us as we embark on an exciting journey to drive a transformational shift in how CVS Health leverages clinical data and analytics to become the leader in consumer healthcare in the U.S.

As a Lead Data Scientist - Clinical Informatics (Clinical Data Standards), you are tasked with activating CVS Health's clinical data repository to improve outcomes across multiple lines of business and use cases. You will serve as a bridge between clinical data assets and the analysts, data scientists, and business partners who consume them—ensuring data is accessible, well-documented, fit for purpose, and aligned with clinical and regulatory standards.

• Serve as a subject matter expert in clinical data, including CCD data, with deep understanding of how to structure and apply this data to solve healthcare problems.
• Design and maintain clinical data models, taxonomies, and classification frameworks that enable consistent interpretation and use of clinical data across the organization.
• Develop and govern the clinical data feature store, establishing standards, documentation, and best practices that accelerate adoption of clinical data for downstream analytics, reporting, and AI/ML use cases.
• Enable self-service analytics by building well-documented, validated, and reusable data assets (tables, views, features) that empower analysts and data scientists to work independently with clinical data.
• Create and maintain comprehensive data documentation, including data dictionaries, lineage, business logic, known limitations, and appropriate use guidelines for clinical datasets.
• Build queries, dashboards, and data visualizations to effectively communicate data quality metrics, data availability, and clinical insights to technical and non-technical stakeholders.
• Partner with clinical, operational, and business stakeholders to understand their data needs, translate requirements into data solutions, and ensure clinical data assets meet their analytical objectives.
• Lead and mentor data scientists, data analysts, and data engineers, providing guidance on clinical data interpretation, appropriate use, and best practices for working with healthcare data.
• Establish data quality frameworks for clinical data, including validation rules, anomaly detection, and monitoring processes to ensure data integrity and reliability.
• Translate clinical concepts into analytical frameworks, ensuring that business partners understand the capabilities and limitations of available clinical data.
• Collaborate with data engineering teams to inform data pipeline development, ensuring clinical data is ingested, transformed, and stored in ways that support downstream analytics needs.
• Contribute to data governance initiatives, including compliance with HIPAA, data privacy regulations, and internal data stewardship policies.
• Develop and deliver training, presentations, and consultations to existing and prospective data consumers on clinical data assets, appropriate use, and analytics opportunities.
• Stay current with clinical data standards (HL7, FHIR, ICD-10, SNOMED-CT, LOINC, CPT, NDC, RxNorm) and industry best practices in clinical informatics.

Qualifications

• 7+ years of relevant experience in clinical informatics, healthcare analytics, or clinical data management.
• Deep expertise in clinical data types and structures, including CCD data, lab results, clinical notes, and administrative healthcare data.
• Strong knowledge of clinical coding systems and terminologies, such as ICD-10, CPT, HCPCS, SNOMED-CT, LOINC, NDC, and RxNorm.
• Experience designing and documenting data models, taxonomies, or classification frameworks for clinical or healthcare data.
• Proven ability to enable and support downstream data consumers (analysts, data scientists, business users) through documentation, training, and consultative support.
• Experience leading cross-functional projects from concept to delivery by coordinating across clinical, technical, and business stakeholders.
• Proficiency with SQL and experience working with large-scale healthcare datasets.
• Experience using cloud-based data platforms, preferably Google Cloud Platform (GCP) tools including BigQuery, for querying, transforming, and managing data.
• Strong understanding of data quality principles, including validation, profiling, and monitoring of healthcare data.
• Excellent written and verbal communication skills, including the ability to explain complex clinical data concepts to both technical and non-technical audiences.
• Ability to anticipate and resolve roadblocks throughout a project lifecycle, balancing competing priorities across multiple stakeholders.

Preferred Qualifications

• Healthcare data platform experience with strong understanding of interoperability standards and harmonization at scale (OMOP/CCDA/FHIR).
• Familiarity with clinical workflows and HIEs.
• Experience using standardized clinical code systems (e.g., ICD-10, SNOMED CT, LOINC, RxNorm, UMLS) and their application within common data models (e.g., OMOP).
• Experience in ETL design & implementation from heterogeneous clinical sources into different data standards preferably into the OMOP CDM.
• Experience designing and implementing data quality frameworks, preferred to have experience with tools like Achilles, Data Quality Dashboard (DQDB), or equivalent custom frameworks.
• Privacy, security, and compliance: HIPAA/HITRUST experience, de-identification/tokenization, PHI handling, and data access controls (column-level, row-level security).

Education

• Bachelor’s degree in health informatics, Public Health, Nursing, Health Information Management, Computer Science, Statistics, or a related quantitative or clinical field—or an equivalent combination of formal education and experience.
• Master's degree or higher in Health Informatics, Biomedical Informatics, Clinical Informatics, Public Health, Epidemiology, or a related field is strongly preferred.
• Clinical background (RN, PharmD, MD, or similar) with transition into informatics/analytics is highly valued.

Pay Range

The typical pay range for this role is: $130,295.00 - $260,590.00. This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company’s equity award program.

Benefits

This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include:

• Medical, dental, and vision coverage
• Paid time off
• Retirement savings options
• Wellness programs
• Other resources, based on eligibility

Additional details about available benefits are provided during the application process and on Benefits Moments.