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Redwood City, California, United States
Hybrid
Not Available
Revolution Medicines is a late-stage clinical oncology company developing novel targeted therapies for patients with RAS-addicted cancers. The company’s R&D pipeline comprises RAS(ON) inhibitors designed to suppress diverse oncogenic variants of RAS proteins. The company’s RAS(ON) inhibitors daraxonrasib (RMC-6236), a RAS(ON) multi-selective inhibitor; elironrasib (RMC-6291), a RAS(ON) G12C-selective inhibitor; zoldonrasib (RMC-9805), a RAS(ON) G12D-selective inhibitor; and RMC-5127, a RAS(ON) G12V-selective inhibitor, are currently in clinical development. 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 an Executive Director and Head of Research Computational Biology within our Biology Function, the individual will oversee the scientific and strategic direction of systems biology research and preclinical computational biology initiatives. The individual will lead a team of computational biologists and bioinformaticians focused on acquisition, organization, and analysis of large multi-omics data sets, using both public and proprietary data sources, that will help inform treatment strategies and guide patient stratification for a growing pipeline of RAS(ON) and targeted oncology therapeutics. We are looking for an experienced leader with strong interpersonal skills and an ability to lead a strong and diverse computational biology team. Key aspects of the role include:
Strategic vision and leadership: Develop and implement a long-term strategy for research systems biology and bioinformatic activities to support a growing pipeline of RAS(ON) and novel targeted inhibitors. Lead and supervise a team of experienced computational biologists and bioinformaticians to generate, organize, and interpret large data sets to inform therapeutic and combination strategies for patients with cancer.
Cross-functional collaboration across research, translational, development and medical affairs groups: Work across functions to support advancement of programs from early discovery into clinical development using biological insights derived from computational approaches. Additionally, leverage clinical data from RVMD investigational agents to generate proprietary insights into RAS mutant tumor biology and RVMD RAS(ON) inhibitor mechanisms of action.
Technical leadership and innovation: Lead a team analyzing large, high-dimensional datasets. Work with colleagues in Information Sciences and Information Systems to oversee data integration, analysis and visualization using cloud-based platforms (AWS, Azure, GCP). Direct the development and application of cutting-edge statistical analysis, AI/ML methods, generative AI models, and MLOps principles to elucidate findings and generate new insights related to biomarker discovery, drug target identification, and predictive modeling. Establish and implement modern workflow management systems (Snakemake, Nextflow) and reproducible research practices.
External collaboration: Cultivate and manage academic and industry collaborations, including CRO partnerships. Represent the company at scientific conferences through presentations and thought leadership. Maintain an active publication record in high-impact, peer reviewed journals. Drive intellectual property strategy and patent filings related to computational discoveries.
Required Skills, Experience and Education:
Education: A Ph.D. in systems biology, computational biology, bioinformatics, or a related biological or biomedical discipline.
Experience: Minimum of 15+ years total experience with significant pharmaceutical/biotechnology industry and management experience.
Scientific knowledge: Deep expertise in systems biology, computational biology, and bioinformatics, including proficiency with multi-omics data integration, modeling, and analysis. Experience with single-cell technologies, spatial transcriptomics, proteomics, and epigenomics. Oncology research experience preferred but not required.
Technical: Advanced programming skills in R, Python, and at least one additional language (Perl, C/C++, Java). Proficiency with high-performance computing (HPC) and cloud platforms (AWS, Azure, or GCP). Knowledge of workflow management tools and version control systems. Understanding of MLOps principles, model deployment, and generative AI applications in drug discovery.
Leadership and management: Demonstrated ability to lead, mentor, and inspire interdisciplinary teams while fostering a collaborative culture. Experience managing budgets and strategic planning at the department level. Proven track record of advancing research programs from discovery through development.
Strategic thinking: Proven strategic thinker who can align research and drug development objectives and leverage innovative technologies effectively.
Communication: Excellent communication and presentation skills for interacting with technical teams, senior leadership, and external partners. #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.
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