Daniel Sabanes Bove

Daniel Sabanes Bove studied statistics and obtained his PhD in 2013 for his research work on Bayesian model selection. He started his career in Roche as a biostatistician and then worked at Google as a data scientist before rejoining Roche, where he is currently leading the Statistical Engineering team within Data Science Acceleration that works on productionizing R packages, Shiny modules and how-to templates for data scientists. Daniel is (co-)author of multiple R packages published on CRAN and Bioconductor, as well as the book Likelihood and Bayesian Inference: With Applications in Biology and Medicine, and is currently chairing the ASA BIOP working group on Software Engineering (SWE WG).

Coursera

Genentech

Making Data Science Work for Clinical Reporting (Coursera)

Statistics & Data Analysis Data Science

Discover how data science can revolutionize your approach to clinical reporting. This course is designed for professionals looking to integrate data-driven insights into their clinical trial documentation processes. Gain a deep understanding of the requirements in clinical reporting and learn practical techniques to apply data science effectively, ensuring accuracy and efficiency every step of the way.

May 18th 2026

4 Weeks

Github Clinical Trials Data Science

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