Strategic Decision Scientist: Causal Analytics Lead

CVS Health; North Dakota; Hybrid; USD 144,000 - 288,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Paid time off

Job summary

CVS Health's Signify Health Strategy & Innovation team seeks a Principal Decision Scientist to design and lead causal inference studies that quantify member outcomes and guide strategic decisions in home health and related services.

This role partners with cross-functional teams and executive leadership, delivering rigorous analyses, scalable data assets, and reusable methodologies while mentoring analytics talent across the organization.

Qualifications

• 10+ years in Decision Science, Data Science, or related quantitative field.
• Expert SQL and Python; experience with large datasets and statistical methods.
• Strong statistics, experimental design, and modeling experience.
• Experience with causal inference and impact measurement.
• Healthcare/payer data expertise and executive communication skills.
• Experience with modern cloud platforms and data engineering practices.

Responsibilities

• Design, build, and maintain causal inference studies to quantify member outcomes.
• Lead deep statistical studies to support strategy and growth opportunities.
• Provide analytic support for strategic evaluations and product/partner sizings.
• Champion analytics best practices and mentor analytics talent across the organization.
• Present analyses to the executive leadership and influence strategic decisions.

Skills

SQL

Python

Causal inference

Executive communication

Healthcare data

Education

Bachelor's degree in quantitative field

Master's degree preferred

Tools

Snowflake

AWS/Azure/GCP

ETL/ELT

Relational/NoSQL databases

Job description

CVS Health's Signify Health Strategy & Innovation team seeks a Principal Decision Scientist to design and lead causal inference studies that quantify member outcomes and guide strategic decisions in home health and related services.

This role partners with cross-functional teams and executive leadership, delivering rigorous analyses, scalable data assets, and reusable methodologies while mentoring analytics talent across the organization.