Gilead Sciences
Senior Scientist, Oncology Research
United States - California - Foster City · Senior
Stay score
odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
This range already reaches Level IV — the maximum four lottery entries.
DOL prevailing wage, 2026-27 wage year · Biological Scientists, All Other (19-1029) · Bakersfield-Delano, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
Employer immigration record
from this employer's Department of Labor filings
Green-card follow-through: 71%
Files H-1B transfers
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
Community outcomes
No reports yet — be the first to help the next applicant.
About the role
- The Oncology Research Department at Gilead Sciences (Foster City, CA) is seeking an accomplished scientist-leader for Senior Scientist of Tumor-Intrinsic Biology.
- Mentor a lab-based scientific team, advancing their projects and careers.
- Serve as a scientific and technical thought leader throughout the Research organization.
Responsibilities
- Collaborate across functions to guide interdisciplinary projects, with experts in oncology, immune-oncology, protein engineering, chemistry, translational medicine, biomarkers and clinical development.
- Develop expertise in relevant scientific fields and the external landscape, including the scientific literature, conference proceedings, and competitive programs.
- Join Gilead and help create possible, together.
Requirements
- Direct experimental and conceptual experience with in vivo models (e.g., genetically engineered mouse models) and the physiological effects of therapeutic intervention.
- Team-centric mindset, with ability to motivate team members from diverse backgrounds.
Nice to have
- Ph.D. degree and 3+ years of experience (tumor biology, drug discovery, target identification and technology development), with post-doctoral training highly preferred.
Skills
- Knowledge, Experience and Skills
- Excellent communication and interpersonal skills.
Compensation
- $169,320.00 - $219,120.00.
- Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location.
- These considerations mean actual compensation will vary.
- This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package.
Benefits
- include company-sponsored medical, dental, vision, and life insurance plans*.
- Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans.
- We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference.
- This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package.
Company info
- At Gilead, we're creating a healthier world for all people.
- Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact.
- As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations.
This listing is sourced directly from Gilead Sciences's careers page and normalized into a canonical job model.