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 Decision Scientist - Clinical Informatics (Clinical Data Standards), 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: 

• Become 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. 

• 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, 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. 

• 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. 

• Learn data governance practices, including compliance with HIPAA, data privacy regulations, and internal data stewardship policies. 

• Stay current with clinical data standards (HL7, FHIR, ICD-10, SNOMED-CT, LOINC, CPT, NDC, RxNorm) and industry best practices in clinical informatics. 

Required Qualifications 

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

• Familiar with clinical data types and structures, including CCD data, 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. 

• Ability to 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. 

• Familiar using cloud-based data platforms, preferably Google Cloud Platform (GCP) tools including BigQuery, for querying, transforming, and managing data. 

• 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 

• 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). 

Education 

• 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.