Michael De Winter is a Full Stack Data Scientist with eight years of experience applying deep learning, remote sensing and predictive modeling to government and commercial problems from Leiden, Netherlands. At Provincie Zuid-Holland he builds end-to-end solutions—traffic CO2 reduction models, satellite image segmentation and preprocessing pipelines—that translate research into measurable climate and policy outcomes. Comfortable across Python, Spark, R, Shiny and JavaScript, he pairs hands-on coding with domain-savvy product thinking developed through consultancy roles for banks and insurers. His background in economics, informatics and computer science underpins a pragmatic approach to data-driven decision making and reproducible workflows, and his public GitHub (MW-88) and provincial repos reveal an emphasis on operational preprocessing for remote sensing rather than just model proof-of-concept work.
8 years of coding experience
4 years of employment as a software developer
VWO - Economie & Maatschappij
Master of Science (M.Sc.), Computer Science and Science Based Business, Master of Science (M.Sc.), Computer Science and Science Based Business at Leiden University
Bachelor of Science (B.S.), Economics and Informatics, Bachelor of Science (B.S.), Economics and Informatics at Erasmus Universiteit Rotterdam
Code which provides capabilities to a kernel pixel based model over a .tif image
Contributions:37 reviews, 15 PRs, 39 pushes in 1 year 8 months
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