Senior Scientist I, Biomarker Sciences/Translational Sciences

revolutionmedicines; Redwood City (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Revolution Medicines is seeking a Senior Scientist I, Biomarker Sciences/Translational Sciences, to join its Translational Research team. You will apply computational approaches to uncover biomarkers, drug response mechanisms, pharmacodynamic effects, and translational insights across studies.

Responsibilities include integrating omics, pathology, and clinical data; developing scalable analytics; and collaborating across Translational Research, Translational Medicine, Discovery, and

Qualifications

• PhD with 4+ years postdoc/industry in oncology drug discovery/development.
• Experience analyzing complex omics datasets (bulk/single-cell, spatial transcriptomics).
• Translate computational findings into testable biological hypotheses and drug-development insights.

Responsibilities

• Apply computational approaches to identify biomarkers and drug response mechanisms.
• Integrate multi-omics and phenotypic data to generate actionable hypotheses.
• Develop reproducible analyses and scalable analytics workflows.

Skills

Cancer biology

Omics data analysis

R/Python

Machine learning

Translational biology

Statistical analysis

Data visualization

Education

PhD in Cancer Biology or related field

Tools

R

Python

Databricks

Job description

The Opportunity:

As a Senior Scientist I, Biomarker Sciences/Translational Sciences, you will be a key member of the Translational Research team, applying computational approaches to derive biological and translational insights from complex preclinical and clinical datasets. You will:

• Translational Science: Apply computational approaches to uncover biomarkers, mechanisms of drug response and resistance, pharmacodynamic effects, and therapeutic strategies across translational studies.
• Omics & Integrated Biology: Analyze and integrate bulk and single-cell sequencing, spatial transcriptomics, and other molecular data with biomarker, pathology, and efficacy/response outcomes to generate actionable biological hypotheses.
• Scalable Analytics: Develop reproducible analytical workflows and partner on AI-enabled solutions that accelerate exploratory data analysis, visualization, and biological interpretation.
• Cross-functional Collaboration: Partner across Translational Research, Translational Medicine, Discovery, Bioinformatics, and Information Sciences to address key scientific questions across the portfolio.
• Analyze and integrate multimodal molecular and phenotypic datasets from translational studies to identify biomarkers, pharmacodynamic effects, mechanisms of response and resistance, and combination hypotheses.
• Perform cross-study analyses to identify reproducible biological signals and translate computational findings into testable mechanistic and translational hypotheses.
• Partner with experimental scientists on study design and testing of computationally derived biological hypotheses.
• Partner with Biomarker Assays teams to translate insights into actionable biomarker analytes.
• Partner with data science and technology teams to translate scientific needs into scalable analytical and visualization solutions.
• Evaluate and apply emerging AI/ML approaches to accelerate analysis, data integration, and biological insight generation.
• Clearly communicate complex analyses and biological conclusions to multidisciplinary project teams and scientific leadership.

Required Skills, Experience and Education:

• PhD in Cancer Biology, Molecular Oncology, Molecular Medicine, Human Genetics, or a related translational biomedical discipline, with 4+ years of relevant postdoctoral and/or industry experience in oncology drug discovery and development.
• Substantial hands-on experience analyzing and biologically interpreting complex omics datasets, including bulk and single-cell sequencing, spatial transcriptomics, and integrated molecular, phenotypic, and clinical/translational data.
• Strong background in oncology, cancer genomics, and translational biology, with demonstrated ability to independently frame biological questions and translate computational findings into testable hypotheses and drug-development insights.
• Demonstrated experience and proficiency in applying and evaluating machine learning and emerging AI-enabled approaches to biological data analysis.
• Proficiency in R and/or Python for the analysis and interpretation of biological data, with a strong commitment to reproducible and rigorous analytical practices.
• Strong foundation in statistical analysis and experimental design for high-dimensional biological and biomarker data.
• Strong collaboration and scientific communication skills, with the ability to communicate actionable conclusions to multidisciplinary audiences.

Preferred Skills:

• Background in oncology drug discovery or development within a biotechnology or pharmaceutical environment.
• Experience analyzing and interpreting longitudinal baseline, on-treatment, and resistance/progression datasets.
• Ability to integrate sequencing data with proteomics, pathology, ctDNA, pharmacology, and/or clinical outcomes.
• Familiarity with cloud-based analytical environments such as Databricks and collaboration on interactive analytical and visualization tools.
• Knowledge of RAS/MAPK biology and RAS-driven cancers.

#LI-SB1 #LI-Hybrid

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