Vice President, Head of Data Product (Research)

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 professionals in a tireless commitment to patients with cancers harboring mutations in the RAS signaling pathway.

The Opportunity: 

As the founding Vice President, Head of Data Product (Research), this role represents a unique opportunity to serve as a central hub in advancing modern data systems to elevate cutting-edge scientific and operational outputs of the research organization. We are seeking an experienced and visionary leader with strong interpersonal skills and an ability to lead through change. This high-impact position reporting to our CSO will:

• Lead efforts to develop and disseminate a cohesive vision for our Research data platform, integrating the long- and short-term needs of data generators and consumers together with the constraints and considerations of technical implementation teams to develop internal data product definitions, specifications, designs, user experiences, prioritizations, and roadmaps.

• Be accountable for implementing data strategy through advancement of modern, scalable data systems that enable state-of-the-art analytics and align with the company’s long-term research and corporate goals. Able to understand and leverage RevMed’s value proposition and define a short- and long-term data strategy that meets the needs of the Research organization.

• Leverage strong cross-functional skills to drive alignment and coordination of data projects involving groups across the organization including research, data science, information sciences, and engineering teams. Able to define and execute on a shared mission and vision across multiple departments, by establishing alignment and key stakeholder buy in to achieve business outcomes.

• Engage with external partners including software engineering firms and consultants, life science SaaS companies, data science and ML/AI partners, and ontologies experts to push forward technical strategy and execution of core data models, infrastructure, and tooling.

• Be accountable for delivering data platform roadmaps, budgets, rollouts, and timelines, aligning with company leadership and ensuring that key stakeholders are engaged, educated, and informed, and supported by robust change management measures.

• Conduct market intelligence to monitor and react to emerging data and analytics trends, ensuring our company stays at the forefront of innovation in the biotech and biopharma drug discovery space.

• Develop and scale a team to successfully achieve business objectives by partnering with the organization to drive outcomes.

Required Skills, Experience, and Education:

• 15 years experience in data product management at diagnostics or therapeutics life sciences companies.

• An entrepreneurial “no task too big or too small” leadership mindset prepared to proactively address any gaps as needed to ensure long-term strategic and tactical success in developing and deploying the data platform.

• Proven leadership orchestrating the development of state-of-the-art data platforms, including the ability to work cross-functionally with biology and chemistry research, information sciences, IT, cybersecurity, and software engineering teams.

• Extensive experience interfacing with internal and external software teams within data engineering, semantics and ontologies, front-end, DevOps, and product management functions, as well as a deep network of contacts within those disciplines.

• Strong project management skills with the ability to develop detailed roadmaps, manage timelines, and align key stakeholders across departments.

• Ability to develop and monitor leading and lagging metrics that inform the success and value-add of data products.

• Familiarity with life science software platforms (e.g. Benchling), cloud-based storage, integration, and compute infrastructures (AWS, Azure, Snowflake, Databricks, etc.), and data security best practices.

• Commitment to observing best practices in software development, including requirements gathering, design, development, testing, deployment, and maintenance.

• Experience coordinating the curation,