2026 Summer Intern - Product Development Data Sciences

Genentech•Daly City, CA

3d•$50 - $50•Onsite

About The Position

Product Development Data Sciences is a group of over 1,000 data scientists across five global sites. We deliver data and insights about our medicine with excellence and passion. Our mission is to unlock the full potential of data to accelerate innovative healthcare solutions for patients and society. This internship position is located in South San Francisco, on-site. The Opportunity Statistical research: Helping solve statistical problems directly relevant to ongoing clinical drug development in diverse therapeutic areas such as oncology, immunology, ophthalmology, neuroscience, cardiovascular, nephrology, and metabolism. The specific topics may include but are not limited to research problems from early to late-stage clinical trials and post-marketing evaluations. Data analytics: Analyze real-world clinical data to derive data-driven clinical impact and business insights. Programming: Developing or refactoring code to create reusable R packages for data processing or visualization; developing innovative automation solutions for data handling and analytics processes. Data engineering: Exploring efficiencies in data flow from raw to analysis-ready data sets. Machine learning research: Suggesting and implementing new methodologies in machine learning for data exploration to enable scientific reverse translation. Innovation: Driving proof of concept work to explore the usage of new software or programming language in a component of our work. Program Highlights Intensive 6 months, full-time (40 hours per week) paid internship. Program start dates are in May/June 2026. A stipend, based on location, will be provided to help alleviate costs associated with the internship. Ownership of challenging and impactful business-critical projects. Work with some of the most talented people in the biotechnology industry.

Requirements

Must be pursuing a Master's Degree (enrolled student).
Must have attained a Master's Degree.
Must be pursuing a PhD (enrolled student).
Must have attained a PhD.
Required Majors: Statistics, Biostatistics, Data Science, Mathematics, Biotechnology or related fields.
Fundamental training in statistical and data science methods; familiarity with clinical trial statistical knowledge is a plus.
Strong programming skills, particularly in R; experience with software development workflow, including versioning and code collaboration with Git.

Nice To Haves

Excellent communication, collaboration, and interpersonal skills.
Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.
Experience handling and analyzing clinical datasets.

Responsibilities

Statistical research: Helping solve statistical problems directly relevant to ongoing clinical drug development in diverse therapeutic areas such as oncology, immunology, ophthalmology, neuroscience, cardiovascular, nephrology, and metabolism. The specific topics may include but are not limited to research problems from early to late-stage clinical trials and post-marketing evaluations.
Data analytics: Analyze real-world clinical data to derive data-driven clinical impact and business insights.
Programming: Developing or refactoring code to create reusable R packages for data processing or visualization; developing innovative automation solutions for data handling and analytics processes.
Data engineering: Exploring efficiencies in data flow from raw to analysis-ready data sets.
Machine learning research: Suggesting and implementing new methodologies in machine learning for data exploration to enable scientific reverse translation.
Innovation: Driving proof of concept work to explore the usage of new software or programming language in a component of our work.