Full Job Description
Position Summary
We're hiring a Decision Scientist to build and extend the models, pricing logic, and financial simulations that support Caremark's sales and underwriting decisions. This is a hands-on, build-oriented role - most of your time will be spent writing Python and SQL that ships into production tools real underwriters and pricing leaders use.
What You'll Do
You'll develop predictive models, risk and profitability logic, and scenario/forecast frameworks that translate claims, contract terms, and market signals into the numbers our deal teams act on. You'll partner with underwriters, pricing actuaries, and finance to translate business questions into testable code - pricing calculators, P&L tools, recurring forecasts, and the rule engines underneath them. Expect to balance a long-running model build, a quick-turn analysis for a sales leader, and a recurring reporting cycle in the same week.
What You'll Bring
- 3+ years of hands-on experience delivering data science or advanced analytics in a regulated, numbers-heavy environment (healthcare, PBM, insurance, banking, or similar)
- Production-quality Python (or R) - not throwaway notebooks - and advanced SQL across complex, multi-source datasets
- Solid statistical fundamentals: regression, classification, clustering, time-series forecasting, hypothesis testing
- Working knowledge of cloud data platforms (GCP, Azure, AWS, or Databricks/Snowflake) and PySpark or equivalent for large-scale data work
- Comfort with financial concepts (margin, loss ratio, premium, retention) - or proven ability to pick them up fast
- Low-maintenance, high-output: takes context and runs, flags own mistakes early, frames every analysis around the decision it supports
Preferred Qualifications
- Experience building pricing models, risk scoring tools, portfolio optimization logic, or financial simulation frameworks
- Familiarity with pharmacy claims data, PBM economics, or actuarial concepts
- Streamlit, Dash, or similar Python application frameworks
- Experience deploying models or analytical tools into production environments
Education
Bachelor's degree in a quantitative field (Statistics, Mathematics, Economics, Computer Science, Engineering, Actuarial Science, or similar) required. Master's degree preferred.
Anticipated Weekly Hours
40
Time Type
Full time
Pay Range
The typical pay range for this role is:
$64,890.00 - $158,620.00
This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.
Great benefits for great people
We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.
This full-time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well-being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.
Additional details about available benefits are provided during the application process and on Benefits Moments.
We anticipate the application window for this opening will close on: 07/15/2026
