Lead Data Scientist - Clinical Informatics (Clinical Data Standards)

CVS Health is dedicated to transforming healthcare through advanced analytics and clinical informatics. The Lead Data Scientist - Clinical Informatics will enhance the clinical data repository to improve health outcomes and ensure data accessibility for various stakeholders.

Responsibilities:

• 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

Requirements:

• 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
• 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)