Principal Statistical Methodology Data Scientist

About the role

Genentech's Statistical Methodology Data Scientists enable the adoption of fit-for-purpose statistical methods to strengthen scientific rigor and decision-making. As a Principal Statistical Methodology Data Scientist, you will work with project teams, biostatisticians and cross-functional stakeholders to prototype solutions such as estimand frameworks, trial simulations and covariate adjustment strategies, and support their adoption through training, templates and open-source tools. You will also represent the company in consortia, scientific working groups and regulatory collaborations.

Key responsibilities

• Serve as a methodological thought partner to study teams, giving expert guidance on complex design and analysis across programs
• Lead the development and institutionalization of methodologies that improve trial and portfolio decisions, such as quantitative go/no-go criteria, simulation frameworks and model-based projections
• Shape understanding of innovative statistical methods through consultation, publications and leadership of education efforts
• Anticipate regulatory trends and integrate relevant methodologies into internal practice while guiding external engagements
• Connect across teams, surfacing recurring challenges and co-creating scalable solutions
• Drive external collaboration through consortia, joint working groups or regulatory-facing initiatives
• Mentor junior staff and influence the strategic direction of Statistical Methodology

Required profile

• PhD in Biostatistics, Statistics, Data Science, Computer Science or a related quantitative discipline
• 6+ years of experience designing and applying advanced analytics to complex biomedical data in clinical trial research
• Deep expertise in statistical computing and advanced modeling, with a track record of novel or custom analytical solutions
• Recognized as a technical expert and thought partner, with experience mentoring others and contributing to internal standards and strategy

Preferred

• Experience developing novel, fit-for-purpose analytical methods for different dataset types
• Demonstrated leadership in designing scalable workflows adopted across projects or teams
• Track record of influencing portfolio- or program-level decisions
• Publications, presentations or white papers, and thought leadership in areas such as AI/ML in translational research, real-world data integration and predictive biomarkers

Relocation benefits are not available. The expected salary range for California is $185,200 - $343,900, with actual pay depending on experience, qualifications and location; a discretionary annual bonus may be available.