About the role

Statistical Methodology Data Scientist enhancing research methodologies at Roche. Supporting decision-making through expert guidance and collaboration with various teams in clinical research.

Responsibilities

You serve as a methodological thought partner to study teams, providing expert guidance on complex design and analysis across programs
You lead the development and institutionalization of methodologies that improve decision-making at trial and portfolio levels (e.g., quantitative go/no-go criteria, simulation frameworks, model-based projections)
You shape cross-functional understanding of innovative statistical methods through consultation, publications, and leadership of education efforts
You anticipate regulatory trends and industry shifts, integrating relevant methodologies into internal practices and guiding external engagements
You act as a connector across teams, surfacing recurring challenges and co-creating scalable solutions to elevate analytical excellence in the organization
You drive external collaboration through active participation in consortia, joint working groups, or regulatory-facing initiatives
You mentor junior staff and influence the strategic direction of Statistical Methodology through thought leadership, vision-setting, and capability building.

You hold a PhD (or equivalent experience) in Data Science, Statistics, Computer Science, or a related quantitative discipline
You have 7 + years of experience designing and applying advanced analytics to complex biomedical data in clinical trial research
You bring deep expertise in statistical computing and advanced modeling, with a track record of developing novel or custom analytical solutions
You are recognized as a technical expert and thought partner within the organization or broader field
You have experience mentoring others and contributing to internal standards, strategy, or capability development
You show respect for cultural differences when interacting with colleagues in the global workplace.
Preferred: Experience developing novel or fit-for-purpose analytical methods for different types of datasets
Demonstrated leadership in designing scalable workflows or frameworks adopted across multiple projects or teams
Track record of influencing portfolio- or program-level decisions through rigorous analytical insights
Publications, presentations, or internal white papers that showcase innovative analytical thinking
Thought leadership in emerging data science areas relevant to pharmaceutical development (e.g., AI/ML in translational research, real-world data integration, predictive biomarkers).