This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
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.
Job Responsibility:
Serve as a subject matter expert in clinical data
Design and maintain clinical data models, taxonomies, and classification frameworks
Build the clinical data feature store
Develop analytics by building well-documented, validated, and reusable data assets
Create and maintain comprehensive data documentation
Build queries, dashboards, and data visualizations
Partner with clinical, operational, and business stakeholders
Maintain data quality frameworks for clinical data
Translate clinical concepts into analytical frameworks
Collaborate with data engineering teams
Contribute to data governance initiatives
Develop and deliver training, presentations, and consultations
Stay current with clinical data standards
Requirements:
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
Nice to have:
Proven experience integrating clinical (CCD/OMOP/FHIR) and administrative (claims) data into unified, patient-centric data models
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
Proven ability to enable downstream data consumers through analytics and well-documented, validated, and reusable data assets
Understanding of healthcare business contexts such as care management, value-based care, quality measurement (HEDIS, Stars), and population health