Senior Scientist, Translational Oncology & Biomarkers

Roche; South San Francisco (CA); Hybrid; USD 142,000 - 263,000; Full time

Job summary

Genentech in South San Francisco seeks a Principal Scientist in Translational Medicine Oncology to lead biomarker discovery and translational strategy across oncology programs, spanning early- to late-stage clinical studies.

You will design end-to-end pharmacodynamic and predictive biomarker strategies, integrate multi-omic data, and collaborate with computational scientists, clinical teams, and KOLs to advance patient outcomes.

Qualifications

• Hold a PhD, MD, or MD/PhD in Molecular Biology, Cancer Biology, Immunology, Computational Biology, Bioinformatics, or a related life sciences discipline.
• Significant graduate or postdoctoral research with first-author publications in peer-reviewed journals.
• Post-graduate industry or substantial postdoctoral experience required.
• Hands-on experience or fluency in translational research methodologies, including molecular profiling, multi-omics, single-cell genomics, spatial biology, or functional immune assays.

Responsibilities

• Design, implement, and drive end-to-end pharmacodynamic and predictive biomarker strategies across clinical studies.
• Champion translational research to identify biomarkers of response, resistance, and tumor microenvironment dynamics.
• Integrate high-dimensional data (multi-omics, spatial biology, single-cell) with computational scientists.
• Lead authoring and integration of biomarker sections in protocols, submissions, and study reports.
• Collaborate across Research, Clinical Development, Biostatistics, and Operations for scientific alignment.

Skills

Cross-functional collaboration

Scientific communication

Translational research

Multi-omics data analysis

Single-cell genomics

Education

PhD/MD in life sciences

Tools

R

Python

Job description

Genentech in South San Francisco seeks a Principal Scientist in Translational Medicine Oncology to lead biomarker discovery and translational strategy across oncology programs, spanning early- to late-stage clinical studies.

You will design end-to-end pharmacodynamic and predictive biomarker strategies, integrate multi-omic data, and collaborate with computational scientists, clinical teams, and KOLs to advance patient outcomes.