Summary
Kader Bouregag is a data scientist with nine years of experience specializing in medical informatics and real-world data at Roche/Genentech, focused on applying ML and LLMs to clinical text and time-series problems. He blends hands-on clinical data engineering (FHIR, OMOP, HL7v2) and terminology expertise (SNOMED, ICD, UMLS) with knowledge-graph integration to unlock siloed healthcare data. Kader has driven OMOP mapping and adverse event detection projects in academic and industry settings, demonstrating an ability to move models from research to regulated environments. A Fulbright and Chevening alum, he pairs dual master’s degrees in Data Science and Health Informatics with practical ETL and production ML experience. Notably, he leverages transformers and generative AI for medical content processing while maintaining strong foundations in standards and interoperability.
9 years of coding experience
2 years of employment as a software developer
Master's degree Health Informatics, Master's degree Health Informatics at Georgetown University
BSc - Eng Information Systems and Technologies, BSc - Eng Information Systems and Technologies at Ecole nationale Superieure d'Informatique (ESI)
Master's degree Data Science, Master's degree Data Science at University of Surrey
French, English, Arabic