Senior Statistical Methodology Data Scientist
Listed on 2026-01-22
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IT/Tech
Data Science Manager, Data Analyst, Data Scientist, AI Engineer
At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come.
Join Roche, where every voice matters.
The Position
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 in Early Development Biometrics (EDB), a core function within Product Development Data Sciences (PDD) that provides strategic leadership and scientific rigor across early clinical development partner across Biostatistics, Analytical Data Science, and Data Management to enable data-driven decision-making from first-in-human through proof-of-concept studies.
As trusted partners in early development, we design efficient and innovative clinical trials, apply rigorous statistical methods, and implement high-quality programming and analytical solutions to accelerate timelines, de-risk development, and increase the probability of technical success. Our integrated teams operate with agility and scientific depth, supporting exploratory analyses, early regulatory engagements, and complex data-generation needs across therapeutic areas. Together, we bring scientific rigor, technical innovation, and strategic insight to shape the future of early development and deliver better outcomes for patients.
Early Development Biometrics is also home to the Statistical Methodology group, which enables the most impactful use of quantitative methodology across PDD through internal consultation, external collaboration, and continuous capability building; and Visual Analytics, which creates and maintains interactive dashboards that drive high-quality Medical Data Review (MDR) and safety signal detection, aligned with Risk-Based Quality Management (RBQM) principles and Critical-to-Quality (CtQ) endpoints.
The Opportunity:The Statistical Methodology Data Scientists play a strategic role in enabling the adoption of fit-for-purpose statistical methodologies to drive scientific rigor and decision-making excellence in early clinical development. This team serves as a center of excellence focused on consultation, education, and outreach to ensure that innovative and appropriate methods are applied across programs and portfolios.
Statistical Methodology Data Scientists collaborate closely with project teams, biostatisticians, and cross‑functional stakeholders to identify methodological needs, prototype solutions (e.g., estimand frameworks, trial simulations, covariate adjustment strategies), and support scalable adoption through training, templates, and tools. They engage in portfolio‑level analyses, scenario modeling, and quantitative frameworks that inform go/no‑go decisions and optimize clinical strategy.
The team also maintains key external relationships, representing the company in consortia, scientific working groups, and regulatory collaborations to stay at the forefront of methodological advances in the pharmaceutical industry.
- You lead or co‑lead methodological consultations with project teams, identifying opportunities to apply fit-for-purpose statistical techniques (e.g., covariate adjustment, trial simulation, Bayesian approaches).
- You develop prototypes or proof‑of‑concept frameworks (e.g., estimand templates, scenario modeling tools) that scale across programs and support consistent decision‑making.
- You translate scientific questions into statistical frameworks that inform strategic trial and portfolio‑level decisions.
- You contribute to internal education by designing and delivering trainings, toolkits, or case study sessions on applied statistical methodology.
- You partner with stakeholders (e.g., TA statisticians, regulatory leads, data science) to pilot, refine, and…
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