Senior Scientist, Biomarkers & Translational Science

Revolution Medicines; San Francisco (CA); On-site; USD 149,000 - 186,000; Full time

Job summary

Revolution Medicines, a global oncology company, seeks a senior translational data scientist to advance biomarker discovery and interpretation across multi-omics datasets. You will couple computational analyses with experimental design guidance to translate findings into actionable insights for RAS-driven cancer programs.

The role emphasizes cross-functional collaboration, scalable analytics, and the application of AI-enabled methods to accelerate understanding of drug response and resistance in

Qualifications

• PhD in Cancer Biology or related translational biomedical discipline (on oncology drug discovery/translation).
• 4+ years postdoc and/or industry experience in oncology drug discovery and development.
• Strong ability to analyze and interpret complex omics datasets (bulk, single-cell, spatial transcriptomics).
• Proficiency in R and/or Python with reproducible analytics; collaboration across functions.

Responsibilities

• Apply translational science approaches to uncover biomarkers, mechanisms of drug response and resistance.
• Analyze and integrate omics data with biomarker, pathology, and efficacy outcomes to generate biological hypotheses.
• Develop reproducible analytics workflows and collaborate on AI-enabled solutions for data analysis and visualization.
• Partner with Translational Research, Bioinformatics, and Information Sciences to address key questions across the portfolio.
• Translate computational findings into testable mechanistic hypotheses and inform drug development.

Skills

Omics data analysis

ML & AI approaches

R and Python

Statistical analysis

Scientific communication

Education

PhD in Cancer Biology or related translational biomedical discipline

Tools

Databricks

Bioconductor

Jupyter

Job description

Revolution Medicines, a global oncology company, seeks a senior translational data scientist to advance biomarker discovery and interpretation across multi-omics datasets. You will couple computational analyses with experimental design guidance to translate findings into actionable insights for RAS-driven cancer programs.

The role emphasizes cross-functional collaboration, scalable analytics, and the application of AI-enabled methods to accelerate understanding of drug response and resistance in