Decision Scientist – Product

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🔥 2 minutes ago

🐊 Florida, North Carolina, +3 more states – Remote

🐊 Florida – Remote 🌲 North Carolina – Remote ⚓ Rhode Island – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $64.9k - $158.6k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

✨ Scientist

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CVS Health

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1963

⚕️ Healthcare Insurance

🛒 Retail

🧘 Wellness

Healthcare Insurance • Retail • Wellness

CVS Health is a leading American healthcare company dedicated to improving health access and affordability. The company focuses on a comprehensive approach that includes health services, health insurance, and pharmacy benefits management. Through its subsidiaries, such as Aetna and CVS Caremark, CVS Health offers a range of services that facilitate wellness, condition management, and affordable prescription drug coverage. CVS Health operates neighborhood pharmacies, provides mail-order pharmacy services, and manages specialty medication programs, aiming to make healthcare convenient and accessible for everyone. Driven by a mission to connect people with essential care services, CVS Health is committed to fostering healthier communities and supporting the wellbeing of all individuals.

📋 Description

• 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 • 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 • balance a long-running model build, a quick-turn analysis for a sales leader, and a recurring reporting cycle in the same week

🎯 Requirements

• 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

🏖️ Benefits

• medical, dental, and vision coverage • paid time off • retirement savings options • wellness programs • comprehensive benefits package designed to support the physical, emotional, and financial well-being of colleagues and their families