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# Biostatistician/Data Scientist in Personalized Healthcare

- **Company:** Roche
- **Location:** Sant Cugat del Vallès, Spain
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, LaTeX, Logistic Regression, Markdown
- **Published:** October 8, 2026
- **Apply:** https://dejobs.org/x/x/BC7E0512290C43EAB680303AC302CBF2/job/

## About the Role

* Education: Degree ( M.Sc ., or Ph.D.) in (Bio)statistics, Mathematics, Data Science, Physics, Epidemiology, or a related quantitative field.
 * Diagnostic Statistics: Foundational understanding of statistical methodologies relevant to diagnostic applications (e.g., ROC curve analysis, cut-off determination, logistic regression, survival analysis, or longitudinal modeling).
 * Technical Toolkit: Strong knowledge of R and report automation tools ( LaTeX , R Markdown , knitr , or Quarto ). Familiarity with AI-assisted coding tools/workflows is a plus.
 * Communication Skills: Ability to break down complex quantitative concepts and communicate them clearly to non-statistical team members. Strong organization and technical documentation skills.
 * Languages: Fluency in English (written and spoken) is required.
 * Preferred : Previous exposure to diagnostic/pharmaceutical research or clinical trial data analysis through internships, working student roles, or academic research projects.

## Description

* Biomarker Development & Data Science: Support the development and validation of novel biomarkers and companion diagnostic assays.
 * Statistical Programming (R): Write, validate, and execute reproducible, high-quality analysis scripts in R to process analytical and clinical datasets.
 * Data Quality & Compliance: Perform code peer-reviews and rigorous quality control checks to ensure data accuracy and adherence to internal SOPs and regulatory standards.
 * Study Planning & Design: Assist in drafting Statistical Analysis Plans (SAPs) and performing sample size/power calculations for analytical and clinical studies.
 * Cross-Functional Collaboration: Partner with interdisciplinary study teams to understand data requirements and present complex statistical findings clearly.

Who You Are

You are a curious, analytical thinker who thrives in a collaborative environment and is passionate about using quantitative methods to advance healthcare.