Senior Data Scientist - Commercial Product Strategy

The Senior Data Scientist will play a critical role in advancing CVS Health’s commercial product strategy by transforming complex healthcare data into actionable insights that drive measurable business outcomes. Supporting Aetna’s Commercial Product organization, this role will focus on developing and scaling advanced analytics solutions—including AI-powered business advisory capabilities—that uncover trends, generate insights, and enable smarter decision-making across a membership base of 15M+ lives.

This individual will operate at the intersection of data science, product strategy, and business leadership, partnering closely with Product, Sales, Actuarial, Marketing, and Underwriting teams to inform product design, pricing strategy, go-to-market execution, and performance optimization. The ideal candidate combines strong technical expertise with business acumen and a proven ability to translate analytics into high-impact growth opportunities and financial results.

• 5+ years of experience in data science, advanced analytics, or analytics consulting (7+ years preferred)
• Proven track record of translating complex data into actionable business insights and measurable outcomes
• Strong proficiency in statistical modeling, machine learning, and data analysis (Python, R, SQL or equivalent)
• Experience working with large, complex datasets (e.g., healthcare claims, customer behavioral data, or similarly structured data)
• Demonstrated ability to influence senior stakeholders and drive cross-functional alignment
• Experience supporting commercial decision-making such as pricing, product strategy, or go-to-market optimization
• Strong problem-solving skills with a focus on identifying high-ROI opportunities
• Excellent communication skills, with the ability to distill complex analyses into clear, strategic recommendations

• Experience in healthcare analytics, particularly with payer/provider data, claims, or population health
• Experience developing AI/ML-driven products or decision-support tools (e.g., recommendation engines, insight platforms, business advisor tools), familiarity with agentic architecture and deployment
• Background in pricing analytics, actuarial partnership, or revenue optimization strategies
• Experience working in product-centric organizations or supporting product lifecycle decisions (inception through optimization)
• Familiarity with experimentation frameworks, causal inference, and advanced forecasting techniques
• Proven ability to lead or mentor junior data scientists and contribute to building high-performing analytics teams
• Experience working in highly matrixed, enterprise environments with executive-level stakeholder engagement
• Strong orientation toward value creation, financial impact, and client-centric outcomes

• Master’s degree (MS) or MBA in a quantitative or business-related field (e.g., Data Science, Statistics, Economics, Engineering, Operations Research, or similar) required
• PhD preferred in a related discipline