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This role is in the Statistical Methodology group, a core function within Product Development Data Sciences (PDD) that strives to enable the most impactful use of quantitative methodology at Roche through internal collaboration, external outreach, and continuous capability building.

THE OPPORTUNITY

The Statistical Methodology group is a core function within Product Development Data Sciences, enabling the impactful use of quantitative methodology across Roche through internal collaboration, external outreach and continuous capability building.

As a Senior Statistical Methodology Data Scientist, you will play a strategic role in advancing the adoption of fit-for-purpose statistical methodologies that strengthen scientific rigor, evidence generation and decision-making across clinical development programs and portfolios. Acting as a methodological thought partner, you will collaborate with study teams, biostatisticians and cross-functional stakeholders to identify needs, prototype solutions and support scalable adoption through training, templates, frameworks and tools.

In this role, you will:

Provide expert methodological guidance to study teams on complex study design, analysis strategies and quantitative decision-making across programs.
Lead the development and implementation of innovative statistical approaches, such as estimand frameworks, trial simulations, covariate adjustment strategies, model-based projections and quantitative go/no-go frameworks.
Translate methodological insights into scalable solutions, including templates, training, open-source tools and best practices that strengthen analytical excellence across the organization.
Support portfolio-level analyses, scenario modeling and quantitative frameworks that inform clinical strategy, optimize development decisions and enable evidence-based prioritization.
Represent Roche externally through scientific collaborations, consortia, working groups, publications or regulatory-facing initiatives, helping the organization stay at the forefront of methodological advances.

WHO YOU ARE

You hold a PhD, in Statistics, Data Science, Computer Science or another related quantitative discipline.
You have 2+ years of experience designing and applying advanced statistical or data science methods to complex biomedical data, ideally in clinical trial research or pharmaceutical development.
You bring strong expertise in statistical computing, advanced modeling and the development of novel or fit-for-purpose analytical solutions for complex datasets.
You are recognized as a technical expert and trusted thought partner, with the ability to translate complex methodology into clear recommendations for scientific, clinical and cross-functional stakeholders.
You have experience contributing to internal standards, capability building, training or strategic initiatives, and you enjoy mentoring others to strengthen methodological understanding and adoption.
You bring a collaborative and inclusive mindset, show respect for cultural differences in a global environment, and ideally have a track record of publications, presentations or thought leadership in emerging areas such as AI/ML, real-world data integration or predictive biomarkers.

Are you ready to make a difference for our patients? We are looking forward to your application – join us now and become part of our journey!

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.

JOB FACTS

Job Sub Category

Statistics

Schedule

Full time

Job Type

Regular

Posted Date

Jun 3rd 2026

Job ID

202605-113105

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