Revolution Medicines is a global, commercial-state oncology company dedicated to discovering, developing and delivering innovative medicines for patients with RAS-addicted cancers. Leveraging its differentiated RAS(ON) tri-complex inhibitor platform, the company is advancing a broad, integrated portfolio of oral RAS(ON) inhibitors designed to directly target the active, cancer-driving state of RAS. Founded on rigorous scientific inquiry and a willingness to challenge long-held assumptions, Revolution Medicines is committed to changing the trajectory of disease for patients with RAS-addicted cancers worldwide.

Our people are united by a shared way of working: follow the science, challenge assumptions, act with urgency and hold ourselves to a high standard of rigor—all in service of patients.

The Opportunity

Reporting to the Director, US Commercial Analytics, the Associate Director, Advanced Analytics & AI Enablement will own the specialist predictive and causal methods that improve targeting, promotional investment, and commercial decisions across Revolution Medicines' portfolio. As RevMed prepares for overlapping launches across multiple cancers, many priority HCPs are likely to be relevant to more than one brand, making it essential to determine which customers to prioritize, for which brands, and at what level of investment.

This is a build role. You will establish patient identification and predictive targeting capability, stand up promotional-effectiveness and marketing-mix measurement, and define the model governance standards that keep methodological ownership inside RevMed. You will also partner on AI-enabled analytics products that move the organization toward trusted, self-service access to commercial data.

This role is ideal for a hands-on quantitative leader who wants to see models activated in real workflows. This position is based out of our headquarters in Redwood City, CA.

Responsibilities:

Patient identification and predictive targeting. Develop and validate patient identification and treatment-progression models using claims, lab, and EHR-derived data; build HCP opportunity, propensity, and affinity scores that inform field and omnichannel targeting across brands.

Promotional effectiveness and investment optimization. Own marketing-mix modeling, execution, and interpretation, including budget and allocation scenarios that inform portfolio promotional investment decisions.

Attribution, causal inference, and incrementality. Lead studies that quantify the true commercial impact of promotional activity, applying appropriate causal methods and clearly communicating assumptions and uncertainty.

Segmentation and next-best-action methods. Develop segmentation, affinity, and next-best-action approaches that support cross-brand customer prioritization where target populations overlap.

Model governance and lifecycle management. Establish validation standards, monitoring scorecards, and refresh cadences for deployed models; decide when a model should scale, be retrained, or be retired based on performance and business impact.

AI enablement for analytics. Partner on AI-enabled analytics use cases, including conversational analytics on commercial dashboards; support metric certification and semantic consistency so AI-delivered answers rest on governed definitions.

Activation and measurement. Partner with Brand Analytics on use-case definition and with Omnichannel Analytics on how model outputs are activated in journeys and triggers and how intervention success is measured.

Collaboration. Partner day-to-day with other analytics leads for routine campaign reporting, field and access dashboards, and production data engineering owned by Information Systems.

Technical self-sufficiency and reuse. Work hands-on in SQL and Python notebooks to query, prototype, and productionize analyses in a modern cloud data platform environment.

Travel as needed and perform other duties as assigned.

Required Skills, Experience and Education

Bachelor's degree in a Science, engineering, or business discipline required, with 6+ years of progressive experience applying advanced analytics in Pharma/Biotech or a comparable commercial environment.