Clinical Data Scientist — Analytics Enablement

Texas Health Institute; Dallas, Northern (TX, KY); Hybrid; USD 83,000 - 222,000; Full time

Job summary

CVS Health is seeking a Senior Data Scientist for Clinical Informatics (Analytics Enablement) to activate clinical data repositories and partner with analysts, data scientists, and business users. You will ensure data is accessible, well-documented, and aligned with regulatory standards to drive analytics, reporting, and AI/ML use cases.

The role emphasizes building reusable data assets, data quality frameworks, and collaboration with data engineering for robust data pipelines across healthcare

Qualifications

• Bachelor's degree in health informatics, public health, nursing, health information management, CS, stats or related field.
• Master's degree or higher strongly preferred.
• Clinical background (RN, PharmD, MD) valued when transitioning into informatics.

Responsibilities

• Serve as SME in clinical data across CCD, claims, pharmacy, labs, and notes.
• Design and maintain clinical data models, taxonomies, and classification frameworks.
• Build the clinical data feature store with standards and documentation.
• Develop analytics by creating validated data assets for analysts and data scientists.
• Create data dictionaries, lineage, and data-use guidelines for clinical datasets.

Skills

Clinical data expertise

SQL

GCP BigQuery

Data governance

Communication skills

Education

Bachelor's degree in health informatics or related field

Master's degree in Health Informatics or related field

Tools

HL7/FHIR

SNOMED-CT

LOINC

Tableau/BI tools

Job description

CVS Health is seeking a Senior Data Scientist for Clinical Informatics (Analytics Enablement) to activate clinical data repositories and partner with analysts, data scientists, and business users. You will ensure data is accessible, well-documented, and aligned with regulatory standards to drive analytics, reporting, and AI/ML use cases.

The role emphasizes building reusable data assets, data quality frameworks, and collaboration with data engineering for robust data pipelines across healthcare