Associate Director, Advanced Analytics & AI Enablement

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.

• Other duties as assigned including travel as needed.

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.

• Demonstrated ownership of predictive modeling and causal methods, including propensity and prediction models, attribution, incrementality, and marketing-mix modeling.

• Deep knowledge of pharmaceutical commercial data assets, including claims, lab, prescription, HCP and account, CRM, and digital engagement data.

• Strong hands-on technical skills in Python or R and SQL, with experience working in cloud analytics environments such as Databricks, Snowflake, or comparable platforms.

• Experience taking models from concept through validation, activation, and monitoring in real business workflows.

• Ability to explain method choice, assumptions, and uncertainty to non-technical commercial leaders and influence decisions accordingly.

• Extensive secondary analytical skills required; ability to translate data and insights into actionable recommendations for business growth.

• Strong problem solver with experience leveraging a variety of research and analytical vendors, study designs, and building quality vendor partnerships.

• Genuine enthusiasm for hands-on technical work: writing SQL and Python in notebook environments, working directly in a modern cloud data platform, and building reusable, well-documented analytical assets.

• Demonstrated use of generative AI tools to accelerate analytical work, such as conversational analytics agents, notebook and code assistants, or comparable capabilities.

• Entrepreneurial mindset, with a tolerance for ambiguity, and a passion for helping cancer patients.

Preferred Skills:

• Advanced degree (MS, PhD, MBA, or equivalent) in statistics, data science, economics, engineering, or a related quantitative field, with 8+ years of progressive experience.

• Targeted oncology or specialty-therapeutics experience, particularly in biomarker-driven markets.

• Experience deploying next-best-action or decisioning frameworks in an omnichannel context.

• Familiarity with conversational analytics, semantic layers, or large language model-based analytics tooling.

• Experience with common commercial data and technology ecosystems such as IQVIA, Komodo, Veeva, Databricks, ThoughtSpot, or Power BI.

#LI-JS1 #LI-Onsite

The base pay salary range for this full-time position for candidates working onsite at our headquarters in Redwood City, CA is listed below. The range displayed on each job posting is intended to be the base pay salary range for an individual working onsite in Redwood City and will be adjusted for the local market a candidate is based in. Our base pay salary ranges are determined by role, level, and location. Individual base pay salary is determined by multiple factors, including job-related skills, experience, market dynamics, and relevant education or training.

Please note that base pay salary range is one part of the overall total rewards program at RevMed, which includes competitive cash compensation, robust equity awards, strong benefits, and significant learning and development opportunities.

Revolution Medicines is an equal opportunity employer and prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity/expression, national origin/ancestry, age, disability, marital status, medical condition, and veteran status.

Revolution Medicines takes protection and security of personal data very seriously and respects your right to privacy while using our website and when contacting us by email or phone. We will only collect, process and use any personal data that you provide to us in accordance with our CCPA Notice and Privacy Policy. For additional information, please contact privacy@revmed.com.

Base Pay Salary Range$186,000-$233,000 USD

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