Yury Kashnitsky has built his career on the boundary between academic and industrial machine learning, and he is one of the few people equally credible on both sides. He holds a Ph.D. in applied mathematics and has earned a place in the Kaggle competitions Master tier, a combination of theoretical depth and competitive, metric-driven practicality that few practitioners achieve.

Today Yury works as a Senior ML Scientist at Elsevier, applying machine learning at scale for the scientific publishing company. His work, and his public talks, focus on the lessons that only production experience teaches: why data science projects fail, how to catch those failures early, when to kill a project, and how to talk to stakeholders about all of it. He has shared these production ML and MLOps lessons on the DataTalks.Club podcast, drawing on experience across academia, startups, and industry.

Yury is also the leader of mlcourse.ai, an open Machine Learning course that grew out of the OpenDataScience community and has guided thousands of learners through rigorous, assignment-driven ML education. He lives in The Hague, the Netherlands, where he continues to look for the right balance between academic and industrial ML.