Summary
Jean-paul Soucy is a data scientist with eight years of experience applying statistical and machine learning methods to healthcare and public health problems. He holds a PhD in epidemiology from the University of Toronto (Vanier Scholar) and has built and maintained complex ETL pipelines and public data APIs used by researchers, journalists, and government during the COVID-19 pandemic. Jean-paul co-led the COVID-19 Canada Open Data Working Group and created the Canadian COVID-19 Data Archive, the largest public collection of pandemic-related Canadian data and documents. He has worked across government, academia, and industry—supporting the Public Health Agency of Canada, advising organizations like WHO, and contributing to AI-driven drug-discovery at Biossil. A seasoned educator and communicator, he has lectured at McGill and written for major outlets on AI and health policy. He combines rigorous epidemiologic training with practical engineering skills to turn heterogeneous health data into actionable insight.
8 years of coding experience
1 year of employment as a software developer
PhD, Epidemiology, PhD, Epidemiology at University of Toronto
Honours BSc, Biology; Minor Mathematics, Honours BSc, Biology; Minor Mathematics at University of Ottawa
MSc, Epidemiology, MSc, Epidemiology at McGill University