Dennis Bakhuis is a data scientist with nine years of experience bridging academic research and applied ML, currently building NLP and deep learning solutions at TenneT and consulting as "Head of Data Science" for a small healthcare practice. He holds a PhD in fluid dynamics and translated that experimental rigor into 13 peer-reviewed publications before pivoting to production-focused ML work such as multi-label BERT models for healthcare text. Highly fluent in Python and the scientific stack, he also teaches deep learning topics and authors practical tutorials for broader adoption. Comfortable in agile teams, he has experience in fraud detection, pipeline management, and end-to-end data tooling. Colleagues value his clear communication and ability to turn complex experimental data into actionable, production-ready models.
9 years of coding experience
7 years of employment as a software developer
Master's Degree, Applied physics, Master's Degree, Applied physics at University of Twente
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