Roche's Early Development Biometrics (EDB) function within Product Development Data Sciences (PDD) aims to solve the business and technical problem of enabling data-driven decision-making from first-in-human through proof-of-concept studies by providing strategic leadership and scientific rigor. The Statistical Methodology Data Scientist role specifically addresses the need for adopting fit-for-purpose statistical methodologies to drive scientific rigor and decision-making excellence in early clinical development, ensuring innovative and appropriate methods are applied across programs and portfolios.
Requirements
- 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.
- 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).
Responsibilities
- 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.
Other
- You hold a Bachelor's degree or a Master’s degree in Data Science, Statistics, Computer Science, Bioinformatics, or a related quantitative field, or comparable mix of education and experience.
- You demonstrate strong collaboration and communication skills, with an eagerness to learn in a fast-paced R&D environment.
- You show respect for সাংস্কৃতিক differences when interacting with colleagues in the global workplace.
- 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.
