Daniel Cervenkov is a data science and physics-trained leader who combines nine years of hands-on high-energy physics research with practical production experience in finance and energy analytics. As Co-Founder and Chief Data Science Officer, he brings expertise in large-scale distributed data analysis, ML-driven modeling, and end-to-end system design honed at CERN, LHCb, and in HFT where his latency and signal work materially boosted trading PnL. He has led multidisciplinary teams to deliver complex hardware-software experiments—one of which passed NASA safety review and is aboard the International Space Station—while also shipping widely used analysis pipelines and a 300% faster particle ID package for a 1,500-user collaboration. Comfortable across simulation, statistics, and production engineering, he blends academic rigor (PhD-level particle physics) with startup pragmatism and a track record of turning hard research problems into deployable solutions.
9 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Elementary Particle Physics, Doctor of Philosophy - PhD, Elementary Particle Physics at Charles University
Contributions:110 commits, 6 PRs, 88 pushes in 3 years 5 months
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