Expert Data Scientist, Early Clinical Development
Genentech · South San Francisco, CA · Data Science & AI / ML
About this role
Genentech is hiring a mid-level Data Scientist based in South San Francisco, CA. The posting calls out experience with Python, R, LLMs, NLP. Compensation is listed at $185,200–$343,900 per year.
- Role
- Data Scientist
- Function
- data engineering
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- South San Francisco, CA
- Department
- Data Science & AI / ML
- Posted
- May 15, 2026
More roles at Genentech
Job description
from Genentech careersThe Position
We advance science so that we all have more time with the people we love.
The Expert Data Scientist is an expert in data visualization, data analysis, data insights, and applied AI/ML-enabled analytics, enabling stakeholders to efficiently and effectively review and analyze data from internal studies and external published data. The Expert Data Scientist works directly with ECD clinical disease area leads, Safety Scientists, and other line function colleagues to ensure that indication- or disease-specific scientific questions are explored thoroughly using creative data analysis, analytical applications, data visualizations, automation, and fit-for-purpose innovation.
Your primary responsibility will be to provide strategic and technical direction for the development, implementation, and continuous improvement of Early Clinical Development data review capabilities at the indication, program, and study level. You will develop scalable solutions and processes that create organizational impact, while continuously identifying opportunities to simplify, automate, innovate, and collaborate with experts within and outside of ECD.
The Expert Data Scientist also manages implementation and adoption of medical data review and visualization applications by providing training, consultation, and dedicated support. The role contributes to ECD portfolio-level review and visualization capabilities, while helping evolve current workflows through automation, data-driven processes, and practical application of AI and advanced technologies where appropriate.