Eugene Shevchuk is a technical advisor and data-driven systems architect who specializes in turning complex data into scalable cloud solutions. Over the past five years he has designed agentic AI systems, a neo-bank risk engine featured in Risk.net, a standalone log analytics platform, and a cross-platform biometric data management stack. He builds robust, scalable deployments with Python, C#, SQL, CI/CD, and infrastructure as code using Terraform and CloudFormation. As a leader, he has guided distributed teams of up to 50 and translates business goals into actionable analytics that drive revenue, including cutting Renmoney’s annual cost from $90k to $10k, speeding model testing from days to seconds, and shortening deployment from 15 days to 3 hours. He holds MITx’s Statistics & Data Science Micromasters and a Harvard University M.S. in Data Science, and he curates MIT Data Science projects on GitHub via f15.dev/request. Based in Moscow, he combines technical depth with strategic communication to deliver data-first solutions that align with business objectives.
9 years of coding experience
14 years of employment as a software developer
Certificate, Querying Data with Transact-SQL, Certificate, Querying Data with Transact-SQL at edX
Bachelor's degree, Applied Mathematics and Computer Science, Bachelor's degree, Applied Mathematics and Computer Science at National Research University of Electronic Technology (MIET)
Micromasters, Statistics & Data Science, 0.95, Micromasters, Statistics & Data Science, 0.95 at MITx on edX
~ HSK3, Chinese Language, ~ HSK3, Chinese Language at East China Normal University
Certificates, Certificates at Udemy
Course, DevOps Deployment Automation with Terraform, AWS and Docker, Course, DevOps Deployment Automation with Terraform, AWS and Docker at LondonApp Developer
Master's degree (HES), Data Science, 3.65, Master's degree (HES), Data Science, 3.65 at Harvard University
Contributions:1 PR, 11 pushes, 2 branches in 8 months
pythonruletask-managertypescriptpipenv
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