Senior Scientist I, Computational Biology, Genomics

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:

• Develop and implement statistical and machine-learning models that link cellular states to phenotypic drug-response readouts and resistance mechanisms.

• Integrate scRNA-seq with bulk RNA-seq, WES, drug-response, and imaging data to build coherent, multi-modal mechanistic hypotheses.

• Prioritize analysis requests, set realistic deliverables, and adapt to evolving project needs while maintaining scientific rigor.

• Effectively communicate complex computational findings to diverse audiences, both internally and externally, through presentations, reports, and publications.

• Serve as a key computational lead, fostering strong collaborations across cross-functional project teams including in vitro and in vivo biologists, chemists, and clinicians, translating complex biological questions into rigorous quantitative tasks and effectively communicating impactful results.

• Provide scientific leadership and mentorship to junior scientists, guiding them through rigorous code reviews, sophisticated experimental-design discussions, and comprehensive career development plans.

Required Skills, Experience and Education:

• Ph.D. in Computational Biology, Biomedical Sciences, Systems Biology, or a related quantitative field.

• 5-8 years (or post-doc plus 3-6 years) industry experience applying computational methods to large-scale genomics data.

• Demonstrated deep expertise and hands-on experience in single-cell transcriptomics analysis using industry-standard tools (e.g., Seurat, Scanpy).

• Strong proficiency in modern statistical modeling and machine learning techniques applied to biological datasets.

• Proficiency in R and Python; experience with workflow languages and containerization.

• Demonstrated ability to translate complex data into clear, testable biological hypotheses, and to influence project direction through data-driven insight.

Preferred Skills:

• Prior experience working in organizations that mine large quantities of cancer genomics data

• Experience deploying scalable computational workflows on cloud platforms (e.g., AWS, Azure) or specialized bioinformatics environments (e.g., DNAnexus), particularly within regulated or clinical-adjacent settings.

• Track record of peer-reviewed publications, conference presentations, or open-source contributions.

• Prior mentoring or line-management experience in a biotech setting.

The base salary range for this full-time position is $144,000 to $180,000 for candidates working onsite at our headquarters in Redwood City, CA. The range displayed on each job posting is intended to be the salary for an individual working onsite in Redwood City and will be adjusted for the local market a candidate is based in. Our salary ranges are determined by role, level, and location. Individual pay is determined by multiple factors, including job-related skills, experience, market dynamics, and relevant education or training.

Please note that 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.

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