Senior Decision Scientist

CVS Health•New York, NY

1d•Remote

About The Position

This role sits at the intersection of product leadership and decision science on Aetna's Care Navigation AI team. You will own the analytical and product vision for AI-powered care guidance experiences — translating complex member needs and clinical signals into scalable, intelligent solutions that help members navigate their health journey with confidence. Partners with clinical, engineering, and product stakeholders to identify, scope, and prioritize opportunities where AI and advanced analytics can meaningfully improve care navigation outcomes Serves as a partial product owner for the care navigation AI roadmap — shaping requirements, driving prioritization decisions, and representing member and business needs through the development lifecycle Collaborates with engineers and data scientists to design and build AI-powered care navigation solutions — including provider selection, cost estimation, and plan benefit interpretation — recommending appropriate modeling approaches and ensuring analytical decisions are grounded in both technical feasibility and member impact Structures analytical work with rigor — defining success metrics, designing experiments, interpreting results, and translating findings into clear product and business recommendations Presents data-driven insights and strategic recommendations to senior leadership and cross-functional stakeholders, with a strong point of view on tradeoffs and priorities Mentors junior data scientists and analysts, elevating team capability in both analytical craft and product thinking Bridges business strategy and technical execution — maintaining an understanding of healthcare industry dynamics, member behavior, and cost/quality levers to inform intelligent solution design Evaluates and communicates technical and business tradeoffs in AI solution design, with accountability for decisions that carry moderate-to-high complexity and organizational impact

Requirements

3+ years of business experience leading analyses and initiatives with a track record of business impact
3+ years experience in strategy consulting or on strategy teams in large companies
Experience acting as a product owner or product partner: writing requirements, driving prioritization, and managing delivery against business outcomes
Proficiency in Python for analytical development and modeling
Strong command of SQL for data access, exploration, and validation
Proven ability to communicate complex analytical concepts clearly to non-technical audiences

Nice To Haves

Experience applying machine learning and AI techniques in a healthcare or care management context (e.g., care gap detection, risk stratification, provider recommendation, conversational AI)
Familiarity with large-scale data environments and modern data platforms (e.g., cloud data warehouses, feature stores, ML pipelines)
Ability to anticipate analytical and product risks early and proactively shape solutions before issues escalate
Strong stakeholder management skills — comfortable influencing without authority across clinical, engineering, and business teams
Experience with agile product development and working alongside engineering teams in sprint-based delivery
People management or formal mentorship experience
Knowledge of healthcare data sources including claims, clinical, pharmacy, and member engagement data

Responsibilities

Partners with clinical, engineering, and product stakeholders to identify, scope, and prioritize opportunities where AI and advanced analytics can meaningfully improve care navigation outcomes
Serves as a partial product owner for the care navigation AI roadmap — shaping requirements, driving prioritization decisions, and representing member and business needs through the development lifecycle
Collaborates with engineers and data scientists to design and build AI-powered care navigation solutions — including provider selection, cost estimation, and plan benefit interpretation — recommending appropriate modeling approaches and ensuring analytical decisions are grounded in both technical feasibility and member impact
Structures analytical work with rigor — defining success metrics, designing experiments, interpreting results, and translating findings into clear product and business recommendations
Presents data-driven insights and strategic recommendations to senior leadership and cross-functional stakeholders, with a strong point of view on tradeoffs and priorities
Mentors junior data scientists and analysts, elevating team capability in both analytical craft and product thinking
Bridges business strategy and technical execution — maintaining an understanding of healthcare industry dynamics, member behavior, and cost/quality levers to inform intelligent solution design
Evaluates and communicates technical and business tradeoffs in AI solution design, with accountability for decisions that carry moderate-to-high complexity and organizational impact