Senior Data Scientist - Clinical Informatics (Analytics Enablement)

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 Senior Data Scientist - Clinical Informatics (Analytics Enablement) , 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.

You will:

• Serve as a subject matter expert in clinical data, including CCD data, claims, pharmacy, lab results, and clinical documentation, withdeepunderstanding 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.
• Build 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.
• Develop 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, andappropriate useguidelines 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 analyticalobjectives.
• Maintain 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.

• 4+ years of relevant experience in clinical informatics, healthcare analytics, or clinical data management.
• 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.
• 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.

Preferred Qualifications

• Proven experience integrating clinical (CCD/OMOP/FHIR) and administrative (claims) data into unified, patient-centric data models, withdeepunderstanding of the strengths, limitations, and complementary nature of each data type.
• Experience with patient data normalization & standardization for patient attributes and cross source harmonization.
• Hands-on experience reconciling clinical and claims data, including diagnosis alignment, medication reconciliation (prescribed vs. dispensed), and encounter/visit matching.
• Experience integrating third-party and enrichment data sources, including SDOH indices (ADI, SVI), consumer/demographic data, mortality data, and provider reference data into patient-level datasets.
• Expert knowledge of clinical and administrative coding systems, including ICD-10-CM/PCS, CPT/HCPCS, SNOMED-CT,RxNorm, NDC, LOINC, and NPI.
• Experience with classification and grouping systems such as HCC, CCS, DRG, and therapeutic class hierarchies.
• Experience designing patient-centric data models, feature stores, and dashboards that aggregate longitudinal data across sources, including demographics, encounters, conditions, medications, labs,utilization, cost, and enrichment attributes
• Proven ability to enable downstream data consumers through analytics and well-documented, validated, and reusable data assets, with experience creating data dictionaries, lineage documentation, and self-service analytics layers.
• Understanding ofhealthcare business contexts such as care management, value-based care, quality measurement (HEDIS, Stars), and population health., * 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.

We're building a world of health around every individual - shaping a more connected, convenient and compassionate health experience. At CVS Health®, you'll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger - helping to simplify health care one person, one family and one community at a time.