Summary
Vladimir Macko is a data scientist and educator with nine years of experience bridging high-energy physics research and applied data science. Currently coordinating the Bachelor of Data Science programme and lecturing at the University of Neuchâtel, he brings hands-on expertise in data engineering, machine learning, statistics and scientific computing honed during a PhD at EPFL and long-term collaborations at CERN. His work spans research, teaching and curriculum design, with a track record of coordinating students and translating complex experimental analysis into reproducible data workflows. Vladimir’s background in LHCb and other international labs gives him uncommon depth in large-scale experimental data pipelines and collaborative scientific software. A quick learner with strong adaptability and team spirit, he combines rigorous quantitative training with a passion for education and technology-driven pedagogy. Based in Renens, Switzerland, he is adept at turning research-grade methods into practical learning experiences for the next generation of data scientists.
9 years of coding experience
8 years of employment as a software developer
Analytics & Data Science Summer School, Deep learning, Analytics & Data Science Summer School, Deep learning at University of Essex
Bachelor of Science - BS, Physics, Bachelor of Science - BS, Physics at Charles University in Prague
University of Oxford
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at EPFL (École polytechnique fédérale de Lausanne)
Master of Science - MS, Physics, Master of Science - MS, Physics at Stockholm University
English, French, Slovak, German, Czech