Decision Scientist, Clinical Informatics & Data Standards

CVS Health; Town of Texas (WI); Hybrid; USD 65,000 - 159,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Paid time off

Retirement options

Job summary

CVS Health is seeking a Decision Scientist - Clinical Informatics to activate the clinical data repository and empower analysts and data scientists to work with high-quality, well-documented data.

You will build a clinical data feature store, maintain comprehensive documentation, develop reusable analytics, and collaborate with engineering to ensure scalable, compliant data pipelines aligned with HIPAA standards.

Qualifications

• 2+ years in clinical informatics or healthcare analytics.
• Familiar with CCD, lab results, and clinical notes.
• Knowledge of ICD-10, CPT, LOINC, RxNorm, SNOMED-CT.

Responsibilities

• Activate CVS Health's clinical data repository and make data accessible to analysts and data scientists.
• Build the clinical data feature store with standards, docs and best practices.
• Develop analytics by creating validated data assets (tables, views, features).
• Create and maintain data dictionaries, lineage and governance details.
• Build dashboards to communicate data quality and insights to stakeholders.
• Translate clinical concepts into analytical frameworks for business partners.
• Collaborate with data engineering to support robust data pipelines under HIPAA.

Skills

Clinical informatics

SQL

Data governance

Documentation

Communication

Healthcare analytics

Education

Bachelor's degree in Health Informatics or related field

Master's degree preferred

Tools

Google Cloud Platform (BigQuery)

ETL tooling

FHIR/HL7 knowledge

Job description

CVS Health is seeking a Decision Scientist - Clinical Informatics to activate the clinical data repository and empower analysts and data scientists to work with high-quality, well-documented data.

You will build a clinical data feature store, maintain comprehensive documentation, develop reusable analytics, and collaborate with engineering to ensure scalable, compliant data pipelines aligned with HIPAA standards.