Vice President, Head Of Data Product Management

Revolution Medicines is a clinical-stage precision oncology company focused on developing novel targeted therapies to inhibit frontier targets in RAS-addicted cancers. The company's R&D pipeline comprises RAS(ON) Inhibitors designed to suppress diverse oncogenic variants of RAS proteins, and RAS Companion Inhibitors for use in combination treatment strategies. As a new member of the Revolution Medicines team, you will join other outstanding Revolutionaries in a tireless commitment to patients with cancers harboring mutations in the RAS signaling pathway.

The Opportunity:

We are pioneering a data-driven discovery and development ecosystem that integrates chemistry, biology, and digital innovation to accelerate insight generation across the R&D continuum - from discovery to clinical development and commercialization.

As the founding Vice President, Head of Data Product Management, this role represents a unique opportunity to define and scale a global data product ecosystem that powers the company's scientific, clinical, commercial, medical affairs, HEOR/RWE, and patient services excellence. This role sits at the intersection of science, technology, and business, enabling data-driven decision making from early research through clinical development and full commercialization.

Reporting to the Chief Digital Officer, you will operate within a hub-and-spoke model, where the central hub drives enterprise-level data product strategy, standards, and architecture, and the spokes consist of Data Product Managers embedded within key functions (Research, Clinical Development, PDM, Commercial, and G&A) who bring deep domain expertise.

You are both visionary and hands-on, capable of designing enterprise-ready data products that power discovery, operational execution, and commercial impact.

Responsibilities:

• Define and Execute the Global Data Product Vision

• Develop a unified, enterprise-wide data product strategy spanning discovery, translational science, clinical development, commercialization, medical affairs, HEOR, market access, marketing analytics, and patient services.

• Define and maintain data product lifecycle frameworks, including schema evolution, version control, metadata standards, and data governance.

• Build, mentor, develop, recruit, and retain talent in your teams; provide leadership to direct reports and non-direct report team members. Ensure training, career development, and performance management.

• Establish and maintain an Enterprise Data Product Catalog and MDM solution covering chemical entities, assay and assay data, biology samples, in vitro and in vivo studies, patient data, real-world datasets, customer and HCP data, market access and payer data, medical insights, and patient service interactions.

• Drive adoption of API-first data contracts to ensure interoperability, reproducibility, and automation across scientific, commercial, and medical systems.

• Develop and govern agent-ready interfaces (e.g., MCP-based tools) that expose data products to AI assistants and automation workflows in a secure, auditable manner.

• Lead the Hub-and-Spoke Operating Model

• Build and manage the central Data Product Management function responsible for architecture, design patterns, product governance, and enterprise alignment.

• Partner with embedded Data Product Managers across Research, Clinical, Commercial, Medical Affairs, HEOR/RWE, Market Access, and Patient Services to ensure each domain's needs are served while meeting global standards.

• Align cross-functional stakeholders across Research, Data Science, IT, Clinical, Commercial, Medical Affairs and G&A to ensure consistent data strategies and product usage.

• Deliver AI- and ML-Optimized Data Products

• Design and oversee modular, scalable data products that serve multiple use cases: analytics, AI model training, GenAI fine-tuning, and operational decision support.

• Collaborate with Data Engineering, CloudOps, MLOps, and Architecture teams to ensure that data products are optimized for high performance, security, and scalability.

• Ensure all data products are compatible with modern AI-driven applications and can fuel predictive modeling and large language model (LLM) training.

• Integrate and Harmonize CRO and External Data Sources

• Develop standardized frameworks and data exchange pipelines with Contract Research Organizations (CROs), academic partners, and external data vendors.

• Implement automated ingestion and validation workflows to ensure data quality, integrity, and compliance.

• Define and enforce metadata, lineage, and security requirements for all external data to ensure harmonization with RevMed's internal data ecosystem.

• Partner with Legal, Compliance, and Procurement to align external data sharing and usage agreements with enterprise data governance policies.

• Govern, Measure, and Evangelize Data Products

• Lead the Data Product Council to set priorities, establish governance, and drive organizational alignment.

• Define and monitor leading and lagging indicators to track adoption, quality, and business impact of data products.

• Champion data culture and literacy across the organization, ensuring scientific and analytical workflows are data product driven.

• Partner Across RevMed and the Broader Ecosystem

• Collaborate with internal technology, research, data scientists, analysts and business partners to ensure enterprise data strategy alignment.

• Engage with external SaaS and data partners (e.g., Benchling, Genedata, Mosaic, IQVIA, Komodo Health, SteepRock, CDD Vault, Knime, Veeva, Posit, Databricks, etc.) to expand data and application capabilities.

• Continuously evaluate and integrate new technologies that enhance the data product portfolio, including GenAI tools, data mesh architectures, and modern cataloging systems.

• Identify, evaluate, and integrate high-value public and open-source biomedical data assets (e.g., protein structure and language model resources, large-scale omics and drug-response datasets) to augment RevMed's internal data ecosystem while ensuring proper licensing, provenance, and scientific alignment.

Example Data Products in Context

• Design-Make-Test-Analyze (DMTA) Data Product: Harmonized chemical and biological entity data, structure-activity relationships, and linked assay metadata.

• Assay Data Product: Standardized experimental output data enabling cross-assay comparisons and downstream analytics.

• Sample & Chain-of-Custody Product: Tracks biological materials and derived datasets from lab bench to clinical study with full traceability.

• Translational Data Product: Unified view of preclinical and clinical data including design, endpoints, and outcomes.

• CRO Data Exchange Product: Standardized interfaces for ingestion, validation, and integration of CRO-generated data.

• Omics Integration & Analysis Data Product: Curated and harmonized genomics, transcriptomics, proteomics, and metabolomics datasets designed to support exploratory analyses, biomarker discovery, and AI-driven feature extraction.

• Insights & ML-Ready Product: Optimized datasets for analytics, predictive modeling, and AI/GenAI applications.

• Protein Folding AI Model Data Product: Datasets and pipelines supporting the training and validation of next-generation protein structure prediction models

• Customer & HCP 360 Data Product: Integrated prescribing, engagement, segmentation, and behavioral datasets.

• Market Access & Payer Analytics Product: Coverage, reimbursement, claims, and payer dynamics data.

• Patient Journey & Support Services Product: Time-to-therapy, adherence, discontinuation drivers, and support-program impact.

• HEOR/RWE Outcomes Product: Claims, EMR, registry, genomic, and survival datasets for real-world value demonstration.

• Medical Affairs Evidence & Insights Product: Engagement insights, scientific influence mapping, congress intelligence.

Required Skills, Experience, and Education:

• 15+ years of experience in data product management or data platform leadership in life sciences, diagnostics, or biopharma.

• Proven record of designing and managing enterprise-grade data products supporting research, development, and commercialization.

• Deep understanding of the scientific data lifecycle and systems used across discovery, translational, and clinical domains.

• Demonstrated experience in defining API contracts, managing evolving schemas, and overseeing metadata frameworks.

• Expertise in cloud-native data platforms (AWS, Azure, Snowflake, Databricks) and modern data governance practices.

• Experience integrating data from CROs, CDMOs, and research partners with rigorous quality and compliance controls.

• Strong technical fluency and ability to communicate across both scientific and engineering stakeholders.

• Skilled in data cataloging, metadata management, data lineage, privacy, and security.

• Excellent leadership and change management skills with a history of influencing across functions.

Preferred Skills:

• Advanced degree in Computer Science, Bioinformatics, or related technical discipline; graduate training in Life Sciences a plus.

• Direct experience in oncology drug discovery or RAS pathway research.

• Familiarity with GenAI and LLM applications in scientific and business domains.

• Experience leading digital transformation or data mesh initiatives in complex organizations

• Experience with GxP requirements and Computer System Validation. #LI-Hybrid #LI-GL1

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

$294,000-$367,000 USD