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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. Position Summary: 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 (Claims Specialization), 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.
Job Responsibility:
Serve as a subject matter expert in clinical data, including claims, pharmacy, lab results, and clinical documentation
Design and maintain clinical data models, taxonomies, and classification frameworks
Develop and govern the claims data feature store
Enable self-service analytics by building well-documented, validated, and reusable data assets
Create and maintain comprehensive data documentation, including data dictionaries, lineage, business logic, known limitations, and appropriate use guidelines
Partner with clinical, operational, and business stakeholders to understand their data needs
Lead and mentor data scientists, data analysts, and data engineers
Establish data quality frameworks for clinical data
Translate clinical concepts into analytical frameworks
Collaborate with data engineering teams to inform data pipeline development
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 data consumers
Stay current with clinical data standards (HL7, FHIR, ICD-10, SNOMED-CT, LOINC, CPT, NDC, RxNorm) and industry best practices.
Requirements:
7+ years of relevant experience in clinical informatics, healthcare analytics, or clinical data management
Deep expertise in clinical data types and structures, including medical claims, pharmacy claims, lab results, clinical notes, and administrative healthcare data
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 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.
Nice to have:
Strong experience with medical claims (professional and institutional), pharmacy claims, and eligibility/enrollment data, including understanding of adjudication, adjustments, and claims completeness considerations
Familiarity with claims-based analytics, including total cost of care, utilization metrics, risk adjustment (HCC), and episode groupers
Strong understanding of interoperability and large‑scale data harmonization across administrative sources and across common standards such as X12, NCPDP, FHIR, and OMOP
Expertise in claims lifecycle and payer workflows, including claim submission, adjudication, pricing, remittance, utilization management, and benefits configuration
Experience working with standardized administrative code systems (e.g., ICD‑10‑CM, CPT/HCPCS, DRG, NDC)
Hands-on experience with ETL pipelines from payer sources into normalized data standards, preferably OMOP CDM with cost and payer domains
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.