Michael Larionov
Staff Data Scientist
Greater Minneapolis-St. Paul Area United States
Summary
👤
Senior🎓
Top SchoolMichael Larionov is a Staff Data Scientist with 11 years of industry experience who combines deep academic training—a Ph.D. in Physics and Mathematics—with practical engineering to ship production-ready AI. Based in the Minneapolis–St. Paul area, he has progressed from developer and consultant roles to senior data architect and data science positions at Honeywell, Resideo, Spok, SurePrep, and now SupportLogic. He specializes in applying Bayesian probability and principled statistical methods to real-world problems, translating research-grade models into robust, deployable systems. Michael is comfortable across platforms and data architectures, bridging the gap between theoretical models and scalable product engineering. His background in physics informs a quantitative, model-driven approach to problem solving that often surfaces simpler, more interpretable solutions than black-box alternatives. Outside of work he maintains developer-focused interests on GitHub, signaling ongoing hands-on engagement with applied data science and tooling.
11 years of coding experience
22 years of employment as a software developer
M.S., Physics, M.S., Physics at Ural State University named after A.M.GorkyDoctor of Philosophy (Ph.D.), Physics and Mathematics, Doctor of Philosophy (Ph.D.), Physics and Mathematics at Donetsk Institute of Physics and Technology
English, Russian, Spanish
Stackoverflow
480reputation
31kreached
11answers
9questions
Github Skills (21)
poc10
categorical8
sampling8
encoding7
bayesian7
netsuite6
loader6
asp-net6
machine-learning6
proxy6
xml-serialization6
viewstate6
x866
msbuild6
browserify5
Programming languages (2)
Github contributions (5)
mlarionov/machine_learning_POC
May 2018 - May 2021
The repository for various machine learning POC
Contributions:81 commits, 1 PR, 64 pushes in 3 years
machine-learningpocdata-science
mlarionov/sampling_bayesian_encoder
Jul 2020 - Nov 2020
Experimental studies of my paper "Sampling Techniques in Bayesian Target Encoding"
Contributions:22 commits, 18 pushes, 2 branches in 4 months
techniquesautoencodersencodingtarget-encodingbayesian
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