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Redwood City, California, United States
Hybrid
Revolution Medicines is a global, commercial-state oncology company dedicated to discovering, developing and delivering innovative medicines for patients with RAS-addicted cancers. Leveraging its differentiated RAS(ON) tri-complex inhibitor platform, the company is advancing a broad, integrated portfolio of oral RAS(ON) inhibitors designed to directly target the active, cancer-driving state of RAS. Founded on rigorous scientific inquiry and a willingness to challenge long-held assumptions, Revolution Medicines is committed to changing the trajectory of disease for patients with RAS-addicted cancers worldwide.
Our people are united by a shared way of working: follow the science, challenge assumptions, act with urgency and hold ourselves to a high standard of rigor—all in service of patients.
The Opportunity:
In this role you will join the Cancer Genomics group in Clinical Biomarker Development, which sits within the Translational Medicine department to develop biomarker, technology, and computational strategies for our RAS(ON) inhibitor programs. You will drive the application of advanced genomics analyses to maximize insight generation from clinical samples in our Phase I-III studies. This role offers the chance to work in a collaborative and innovative environment, including on cross-functional teams with other computational scientists, biomarker leads, biostatisticians, and preclinical scientists.
As a Cancer Genomics Scientist II in Clinical Biomarker Development, you will:
Apply advanced analytics and genomics solutions to clinical biomarker data to inform research & development.
Integrate multi-omics datasets to interrogate disease biology and prognosis, mechanisms of resistance, and predict drug response.
Collaborate with cross functional teams, managing interactions with key stakeholders to deliver robust biomarker analyses and recommend follow up actions.
Communicate results to expert and non-expert audiences, including internal cross-functional team members and external collaborators, through scientific publications and presentations.
Required Skills, Experience, and Education:
A Ph.D. in Cancer Genomics, Genetics, Computational Biology, Bioinformatics, or similar degree.
A minimum of 2 - 6 years post-PhD experience analyzing cancer genomics data (post-doc, biotech, pharma, diagnostics, or combination).
A strong foundation in cancer biology, preferably with an understanding of RAS/MAPK signaling pathways in pancreatic, lung, or colorectal cancer.
Proficiency programming in R and/or Python, and expert in clearly documenting work with a version control system (git).
Experienced in Linux and the cloud, including HPC clusters and command line interface, and developing genomics workflows for large scale NGS datasets.
Experienced analyzing ctDNA or other liquid biopsy data derived from blood samples.
Experienced in the interrogation of DNA sequence data derived from tumor tissue, such as gene-panel, whole-exome or whole-genome data and downstream analytics (clonality estimates, copy number variation, chromosomal instability, mutational signatures, etc).
Practiced in commonly used tools and methods for DNA data analysis (GATK, Bioconductor, etc) and in utilizing publicly available datasets (TCGA, cBioPortal) to interrogate cancer genomics data.
Strong understanding of statistics and the ability to generate robust predictive models with multidimensional data.
Strong interpersonal, verbal and written communication skills; proactive, self-motivated, and adaptable in a dynamic environment.
Demonstrated ability to translate complex data into clear biological insight, and to influence project direction through data-driven scientific inquiry.
Preferred Skills:
Experienced analyzing clinical endpoints (ORR, PFS, OS) including survival analysis.
Longitudinal ctDNA data analysis for predicting clinical endpoints (ORR, PFS, OS).
Deep knowledge of pancreatic, lung, or colorectal cancer, preferably including how progression, response and resistance may be mediated by biomarkers detected in tissue and/or blood biomarkers.
#LI-Hybrid #LI-EM1
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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We are aware of recent recruitment scams in which individuals or organizations falsely represent themselves as being affiliated with Revolution Medicines. These scams may appear as false job advertisements or unsolicited contacts through communication or chat platforms, email, phone, or text message.
Please note that Revolution Medicines does not extend unsolicited employment offers and will never ask candidates to provide financial information, purchase equipment, or pay fees as part of the hiring process. All legitimate communication from Revolution Medicines will come from an official @revmed.com email address.
If you believe you’ve been contacted by someone impersonating a Revolution Medicines recruiter, please report it to careers@revmed.com so we can share these impersonations with our IT team for tracking and awareness.
