Compensation Overview

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

The Opportunity

Playing a critical role as the leader of Computational Chemistry.

• Guide the strategy for expanding the capabilities of structure based drug design within RevMed’s unique mode of action

• Grow the capabilities and leverage modern ML methodology to improve the efficiency of our design cycle

• Managing, coaching and mentoring scientists across the computational chemistry function in order to develop their skills and build RevMed’s organizational capabilities

• Being a partner in the scientific activities of other outstanding scientists across Revolution Medicines and helping create an environment where we channel scientific curiosity to build and deliver a sustainable portfolio

• Advancing the RevMed Research Portfolio and helping build our scientific reputation through presentation/publication of project results in scientific meetings and peer-reviewed literature, as guided by RevMed publication policies, to build our scientific reputation

• Identifying, establishing and leading partnerships with selected strategic technology partners focused on supporting RevMed projects

Required Skills, Experience and Education:

• Ph.D. degree in a relevant scientific discipline with over 15+ years’ experience in the pharmaceutical/biotech industry alongside a strong track record of positive impact in programs

• Expertise in a broad variety of computational techniques is essential, particularly molecular docking, pharmacophore development, library design and analysis, machine learning methods, and protein-protein/protein-ligand simulation

• Experience in applying ML methods to garner new insights or drive program direction

• Recognized as an intellectual leader in the early phases of drug discovery with a track record of patents, publications and project achievements

• Demonstrates ability to recognize anomalous and inconsistent results and interpret experimental outcomes

• Demonstrated ability to plan and achieve research goals as part of an interdisciplinary team

• Knowledge of oncology therapeutic area and drug discovery

• Excellent written and verbal communication skills to work with interdepartmental teams

• Evidence of successful coaching, mentorship and development of both individuals and teams in order to build long-term organizational capability

Preferred Skills:

• Experience in identifying hits and leads against challenging targets using state-of-the-art in silico methodology

• Experience in molecular glues, PROTAC, or other protein-protein interaction modalities

The expected salary range for this role is $235,000 to $281,000. An individual’s position within the range may be influenced by multiple factors, including skills and experience in role, overall performance, individual impact and contributions, tenure, and market dynamics. Base salary 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 [email protected].

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