Summary
Alexey Lyutov is a Senior Data Scientist with a PhD in Mathematics and Computer Science and eight years of experience turning complex industrial problems into production-ready ML solutions. He has built multimodal deep learning systems and internal libraries to accelerate team workflows, led defect prediction and process-optimization projects in steel production, and delivered dashboards that make ML outputs actionable for non-technical stakeholders. His background in CFD, optimization and anomaly detection spans academia and industry—from improving turbine efficiency to uncovering 100+ hidden production issues with unsupervised methods. Notably, he translated NLP research into a decision-support system that cut document processing from two weeks to an hour, and designed supply-network models inspired by biological networks to improve robustness. Based in Düsseldorf, he mentors junior engineers and focuses on reproducible, Git-driven experimentation that bridges research rigor with measurable operational impact.
8 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy - PhD, Mathematics and Computer Science, Doctor of Philosophy - PhD, Mathematics and Computer Science at Jacobs University Bremen
Master of Science (MS), Mathematics, Master of Science (MS), Mathematics at Novosibirsk State University (NSU)
Russian, English, German