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The Position

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 at Roche. We 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 Methods Collaboration & Outreach (MCO), 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.

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 contribute to the development and implementation of appropriate statistical methodologies to address emerging scientific and strategic questions in early development

• You support trial strategy through simulation and exploratory work aligned with estimands, covariate adjustment, or innovative design elements

• You assist in identifying and testing methods that address recurring analytic challenges across multiple projects

• You collaborate with biostatisticians and data scientists to assess the appropriateness of methodological approaches and tools in specific project contexts

• You support documentation, communication, and training efforts that promote adoption of new or complex methodologies

• You engage in foundational outreach activities, such as literature reviews or benchmarking exercises, to stay informed of advances in clinical trial methods

• You participate in working groups focused on methodological education, tool development, or feedback collection from project teams

• You work under general supervision and apply independent judgment to interpret guidance, prioritize responsibilities, and make decisions in situations that require contextual understanding

Who you are:

• You hold a Master’s degree in Data Science, Statistics, Computer Science, Bioinformatics, or a related quantitative field

• You have 2+ years of hands-on experience applying data science or statistical methods to biomedical or clinical datasets (internship or academic experience considered)

• You are proficient in programming languages such as R or Python for data manipulation, modeling, and visualization

• You are familiar with exploratory data analysis, statistical modeling, and common machine learning techniques

• You can work effectively with complex, noisy, or sparse data in early-phase settings

• You demonstrate strong collaboration and communication skills, with an eagerness to learn in a fast-paced R&D environment

• You show respect for cultural differences when interacting with colleagues in the global workplace

Preferred Qualifications:

• Experience working with clinical trial or biomarker datasets

• Exposure to exploratory data analysis methods and visualization tools (e.g., ggplot2, seaborn, plotly)

• Familiarity with tools for reproducible science (e.g., Git, RMarkdown, Jupyter Notebooks)

• Understanding of the early clinical development process and common data challenges (e.g., small sample sizes, high variability)

• Ability to learn and apply new tools or analytical frameworks with guidance

• Demonstrated curiosity and interest in translational science, omics, or real-world data applications

Relocation benefits are not available for this posting

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Who we are

A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.

Let’s build a healthier future, together.