Vice President, Head of Data Product Management

Revolution Medicines•Redwood City, CA

19h•Hybrid

About The Position

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.

Requirements

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.

Nice To Haves

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.

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.