Senior Data Scientist - Clinical Informatics (Claims Specialization)

CVS Health is dedicated to shaping a more connected and compassionate health experience. As a Senior Data Scientist - Clinical Informatics, you will activate CVS Health's clinical data repository to improve healthcare outcomes and serve as a bridge between clinical data assets and various stakeholders, ensuring data accessibility and compliance with standards.

Responsibilities:

• Serve as a subject matter expert in clinical data, including claims 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
• Build the claims 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, 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
• 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
• Understand data governance initiatives, including compliance with HIPAA, data privacy regulations, and internal data stewardship policies
• Develop and deliver 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

Requirements:

• 4+ years of relevant experience in clinical informatics, healthcare analytics, or clinical data management
• Expertise in clinical data types and structures, including claims, 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
• 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 (e.g., medical & pharmacy claims, enrollment/eligibility files, provider files) 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