Summary
Thomas Stricker is a data scientist based in Geneva with 10 years of experience building and governing decision-critical data systems for high-stakes public health environments. He blends deep academic training (PhD in Analytical Chemistry) with practical skills in bioinformatics, SQL/NoSQL data engineering, and machine learning to support surveillance, variant classification, and laboratory information management. His roles at WHO, the Swiss Federal Office of Public Health, and Medisupport show a track record of turning complex biomedical data into actionable analytics, dashboards, and reproducible tools using Python, R, Azure, and Power BI. Equally comfortable writing production .NET/Angular services and R/Shiny apps, he bridges the gap between genetics teams and informatics to accelerate project delivery. Thomas often automates data pipelines and implements robust data quality controls for policy‑relevant decisions, a strength born from combining wet‑lab understanding with software engineering. Though his GitHub is still being populated, his career demonstrates a pattern of shipping pragmatic, well-documented solutions that sit at the intersection of research and operational public health.
10 years of coding experience
9 years of employment as a software developer
Bachelor's degree, Biology, Bachelor's degree in Biology, Bachelor's degree, Biology, Bachelor's degree in Biology at University of Geneva
Certification in Applied Data Science and Machine Learning, Data Science, Open Studies Diploma, Certification in Applied Data Science and Machine Learning, Data Science, Open Studies Diploma at EPFL Extension School
French, English, German, Chinese