Senior Biostatistician (Translational and Exploratory Biostatistics)
Genentech
- Location
- South San Francisco, California, United States of America
- Employment
- Full Time
- Work model
- On-Site
- Level
- Senior
- Posted
- Aug 26, 2026
Skills
About this role
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche. This role is within Biostatistics, a core function within Product Development Data Science and Analytics (PDD) that provides strategic leadership and scientific rigor across Development at Roche. Biostatistics identifies opportunities to apply the full breadth of data, digital, and design capabilities to deploy innovative methods across PDD, PD and the broader Roche Pharma organization. As trusted analytical partners in end-to-end drug development, Biostatistics leverages data to drive scientifically rigorous programmatic decisions across Roche’s Development portfolio; Biostatistics designs robust trials and analysis plans that increase the probability of technical success, accelerating timelines to advance Roche’s clinical pipeline and promote regulatory success — ultimately bringing medicines to our patients faster.
The Opportunity
The Senior Biostatistician will work across diverse therapeutic areas – including Ophthalmology, Cardiovascular, Renal, and Metabolism (CVRM), and Immunology portfolios—serving as a key statistical partner at the intersection of statistics, data science, and clinical development. In this dynamic role, you will balance core clinical trial operations with cutting-edge translational research. You will be responsible for providing strategic statistical input and hands-on execution for both traditional late-phase studies and complex exploratory initiatives, utilizing multimodal data – including biomarkers, imaging, and digital health measurements – to advance high-value work and inform molecule-level development decisions. As a primary statistical partner within cross-functional teams, you will ensure scientific rigor and analytical excellence. You will analyze diverse and complex datasets, implement advanced methodologies, and build robust evidence required to support strategic decision-making and global regulatory submissions.
Your Responsibilities
You drive the statistical execution and contribute to the analytical strategy for a diverse portfolio of work, ranging from clinical study deliverables to complex translational and exploratory initiatives, ensuring scientific integrity across the board. You perform hands-on analysis of multimodal data, researching and implementing advanced statistical methodologies and predictive modeling to address complex clinical challenges. You provide end-to-end statistical support for traditional clinical trials, which includes contributing to study design, protocol development, authoring Statistical Analysis Plans (SAPs), and supporting Clinical Study Reports (CSRs) for regulatory submissions. You act as a key statistical partner on cross-functional teams, collaborating proactively to translate complex data into clear communications and actionable insights for internal and external stakeholders. You represent Biostatistics and PDD on cross-functional project teams, ensuring the statistical rigor of study deliverables. You maintain up-to-date expertise in the latest developments within the fields of statistics, machine learning, and data science to ensure the application of the most appropriate analytical approaches. You provide functional guidance and informal mentorship to less experienced statisticians or data scientists.
Who You Are
You hold a PhD or MSc in Statistics, Biostatistics, Machine Learning, or a closely related quantitative discipline. You have a minimum of 3 years of relevant experience in clinical trial statistics or applied data science within a pharmaceutical, biotech, or CRO setting. You possess demonstrated experience in the analysis of multimodal data and the hands-on application of advanced statistical methods to drive data-informed