Revolution Medicines
Scientist I, Clinical Biomarker Development (Cancer Genomics)
Revolution Medicines, San Francisco, California, United States, 94199
Scientist I, Clinical Biomarker Development (Cancer 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 Revolutionaries in a tireless commitment to patients with cancers harboring mutations in the RAS signaling pathway.
Opportunity In this role you will join the Cancer Genomics group within Clinical Biomarker Development, which sits in 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 & emerging NGS technologies 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.
Responsibilities
Apply advanced analytics and genomics solutions to clinical biomarker data to inform research & development, including machine learning methods with high throughput NGS genomic data.
Integrate multi‑omics datasets (e.g. spatial transcriptomics, liquid biopsy, and other NGS approaches) to interrogate disease biology, resistance mechanisms, 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, or a similar degree in which cancer biology is integrated with genomics data analysis.
Proficiency in programming in R and/or Python for computational biology analysis.
Expert in clearly documenting work with a version control system (git).
Experienced in Linux and the cloud, including HPC clusters and command line interface.
Practiced at developing genomics workflows for large‑scale NGS datasets.
Expert in the interrogation of RNA‑seq data, such as bulk, single‑cell, and spatial transcriptomics data, preferably including utilization of single‑cell atlas data to inform analysis flow.
Experienced working with DNA sequence data (mutation, liquid biopsy, CGP, WES, or similar).
Practiced in commonly used tools and methods (Seurat, Scanpy, GATK, Bioconductor, etc.) and in utilizing publicly available datasets (TCGA, cBioPortal) to interrogate cancer genomics 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 with AI/ML approaches to integrate single‑cell & spatial transcriptomics data.
Deep knowledge of pancreatic cancer, preferably including how progression, response and resistance may be mediated by tumor microenvironment and/or transcriptional programming.
Trained in cancer signaling biology with strong understanding of RAS/MAPK signaling pathways.
Strong understanding of statistics and the ability to generate robust predictive models for outcomes in multidimensional data.
Base Pay Salary Range $115,000 — $144,000 USD
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.
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 CCAA Notice and Privacy Policy. For additional information, please contact privacy@revmed.com.
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Opportunity In this role you will join the Cancer Genomics group within Clinical Biomarker Development, which sits in 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 & emerging NGS technologies 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.
Responsibilities
Apply advanced analytics and genomics solutions to clinical biomarker data to inform research & development, including machine learning methods with high throughput NGS genomic data.
Integrate multi‑omics datasets (e.g. spatial transcriptomics, liquid biopsy, and other NGS approaches) to interrogate disease biology, resistance mechanisms, 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, or a similar degree in which cancer biology is integrated with genomics data analysis.
Proficiency in programming in R and/or Python for computational biology analysis.
Expert in clearly documenting work with a version control system (git).
Experienced in Linux and the cloud, including HPC clusters and command line interface.
Practiced at developing genomics workflows for large‑scale NGS datasets.
Expert in the interrogation of RNA‑seq data, such as bulk, single‑cell, and spatial transcriptomics data, preferably including utilization of single‑cell atlas data to inform analysis flow.
Experienced working with DNA sequence data (mutation, liquid biopsy, CGP, WES, or similar).
Practiced in commonly used tools and methods (Seurat, Scanpy, GATK, Bioconductor, etc.) and in utilizing publicly available datasets (TCGA, cBioPortal) to interrogate cancer genomics 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 with AI/ML approaches to integrate single‑cell & spatial transcriptomics data.
Deep knowledge of pancreatic cancer, preferably including how progression, response and resistance may be mediated by tumor microenvironment and/or transcriptional programming.
Trained in cancer signaling biology with strong understanding of RAS/MAPK signaling pathways.
Strong understanding of statistics and the ability to generate robust predictive models for outcomes in multidimensional data.
Base Pay Salary Range $115,000 — $144,000 USD
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.
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 CCAA Notice and Privacy Policy. For additional information, please contact privacy@revmed.com.
#J-18808-Ljbffr