Genentech's Translational Medicine Oncology(TM ONC) Department supports the entire R&D portfolio of novel therapies. We develop and implement biomarker strategies to study disease pathways, confirm a therapeutic's mechanism of action, and improve clinical trial efficiency and success. Biomarker scientists within our department are responsible for conducting biomarker discovery, developing biomarker strategies, designing and implementing biomarker assays, and interpreting biomarker results. Additionally, we conduct foundational clinical translational research to study the molecular and cellular pathways driving disease to generate novel target and biomarker approaches.
We are seeking an exceptional translational scientist to help shape the next generation of precision oncology. This role sits at the intersection of translational biology, emerging profiling technologies, clinical development, and computational science, with a focus on uncovering novel disease biology from large-scale patient datasets and clinical trial biospecimens.
The successful candidate will design innovative translational research strategies that integrate multimodal molecular profiling, clinical data, and advanced computational approaches to generate actionable biological insights. Working closely with computational biologists, statisticians, and AI/ML scientists, this individual will help identify novel disease states, resistance mechanisms, biomarkers, and patient populations that may inform future oncology treatments.
This role offers a unique opportunity to leverage large-scale patient cohorts, clinical trial biospecimens, and emerging technologies to address previously intractable questions in cancer biology. The successful candidate will play a key role in translating biological questions into fit-for-purpose data generation strategies and partnering across disciplines to transform complex multimodal datasets into insights that influence biomarker strategies, patient stratification, and future therapeutic development.
This role is ideal for a scientist who is excited by scientific discovery, technology innovation, and the opportunity to combine biology and data science to advance precision medicine for patients.
Key Responsibilities
Co-design translational research strategies that address key biological and clinical questions across oncology programs.
Leverage large-scale patient cohorts, clinical trial biospecimens, and multimodal datasets to generate molecule-specific, mechanism-specific, and disease-specific insights.
Identify novel disease states, resistance mechanisms, biomarkers, and patient populations that may inform future oncology treatments.
Evaluate and champion emerging profiling technologies, including genomic, spatial, proteomic, liquid biopsy, single-cell, multimodal, and AI-enabled approaches.
Guide tumor profiling and assay selection for correlative studies, balancing scientific objectives, sample constraints, technical feasibility, and clinical development needs.
Lead fit-for-purpose biomarker study design, including cohort selection, assay strategy, benchmarking, quality control, analytical workflows, and data interpretation.
Partner with biologists, laboratory scientists, computational biologists, statisticians, and AI/ML scientists to integrate data and translate findings into actionable hypotheses.
Contribute to biomarker plans, translational medicine strategies, study protocols, publications, scientific communications, and external collaborations.
Communicate scientific insights and strategic recommendations to multidisciplinary teams, clinical teams, and senior stakeholders.
Who You Are
PhD in Cancer Biology, Molecular Biology, Immunology, Genomics, Bioinformatics, Computational Biology, or a related discipline.
Postdoctoral training or 3+ years of relevant industry or academic experience in translational oncology research.
Strong understanding of current and emerging tumor profiling technologies, including genomic, spatial, proteomic, liquid biopsy, single-cell, or multimodal approaches.
Demonstrated experience with translational study design, including assay selection, technical benchmarking, quality control, analytical workflows, and biological interpretation.
Ability to work effectively across multidisciplinary teams spanning biology, clinical development, laboratory sciences, computational biology, statistics, and AI/ML.
Deep expertise in at least one oncology therapeutic area, such as breast, lung, colorectal, prostate, or hematologic malignancies.
Preferred Qualifications
Experience supporting translational research within academic, clinical or commercial settings
Experience with statistical modeling, biomarker analysis, or multimodal data integration.
Experience evaluating or implementing novel profiling technologies in translational or clinical research.
Experience in leveraging AI models and tools to support productivity
Track record of publications, presentations, or contributions to biomarker development or precision oncology programs.
The expected salary range for this position based on the primary location of California is $120,700 - $224,100 Annual. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits..
Relocation benefits are not available for this position.
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
Skills Required
- PhD in Cancer Biology, Molecular Biology, Immunology, Genomics, Bioinformatics, Computational Biology, or related discipline.
- Postdoctoral training or 3+ years of relevant industry or academic experience in translational oncology research.
- Strong understanding of tumor profiling technologies (genomic, spatial, proteomic, liquid biopsy, single-cell, multimodal).
- Demonstrated experience with translational study design including assay selection, benchmarking, quality control, analytical workflows, and interpretation.
- Ability to work effectively across multidisciplinary teams including biology, clinical development, laboratory sciences, computational biology, statistics, and AI/ML.
- Deep expertise in at least one oncology therapeutic area (e.g., breast, lung, colorectal, prostate, hematologic malignancies).
- Experience supporting translational research within academic, clinical, or commercial settings.
- Experience with statistical modeling, biomarker analysis, or multimodal data integration.
- Experience evaluating or implementing novel profiling technologies in translational or clinical research.
- Experience leveraging AI models and tools to support productivity.
- Track record of publications, presentations, or contributions to biomarker development or precision oncology programs.
Genentech Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Genentech and has not been reviewed or approved by Genentech.
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Healthcare Strength — Health coverage is described as comprehensive across medical, dental, vision, mental health, and prescriptions, supported by HSAs/FSAs and broad wellness resources. On‑site fitness and health centers, mental‑health clinicians, and specialized programs like fully covered preventive cancer screenings and menopause support deepen the offering.
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Retirement Support — Retirement benefits feature a 401(k) with up to a 4% company match plus an additional annual 6% company contribution to eligible pay. Additional financial protections such as life and accident insurance complement salary, bonuses, and stock options.
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Leave & Time Off Breadth — Time away includes about 20 paid vacation days, paid holidays, personal days, and a year‑end shutdown. A paid six‑week sabbatical every six years notably expands long‑term time‑off flexibility.
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