Frédérik Paradis

Before joining Baseline, Frédérik was part of the Pricing Data Science team at Ticketmaster. At the heart of technical decisions and architecture, he managed the team's data infrastructure and machine learning pipelines, all the way to a proof of concept for automated pricing, while handling the most complex implementations and significant work exploring unknowns. His role, however, extended beyond purely technical aspects: in constant dialogue with product owners, he helped prioritize what was feasible, shape the roadmap, and break down the work into concrete tasks. Responsible for code reviews and overall quality, he also ensured that development practices were improved while remaining simple and accessible to other data scientists.

Frédérik holds a bachelor's degree in computer science from Université Laval and a master's degree from the University of Ottawa. He pursued doctoral studies, where he developed a particular interest in deep learning. He then focused on the interpretability of deep neural networks. It was also during this period that he created the Poutyne deep learning library from scratch, aiming to simplify the development of these networks and eliminate repetitive code. This rigorous approach extends his experience as an instructor, from teaching assistant to lecturer, and his role as a reviewer for papers at the prestigious NeurIPS conference.