Alexey P
Senior Product Manager at Constructor
Belgrade, Central Serbia
Summary
👤
Senior🎓
Top SchoolAlexey P is a Senior Product Manager based in Belgrade with 15 years building technical products and a decade of hands-on product delivery across cloud, logistics, and consumer services. He has led cross-functional teams of up to 10 engineers to launch high-throughput backend systems, analytics platforms and mobile apps, most recently directing development for Yandex Datalens and now steering product at Constructor. Alexey pairs a strong engineering foundation (Master’s in Informatics and early experience as a system and QA engineer) with practical product craft—mockups, feature design, A/B testing and analytics-driven iterations—to reduce ops costs and automate workflows. He has a track record of hiring and scaling teams from scratch and shipping client-focused integrations that improved transparency and mitigated financial risk. Beyond product management, he contributes to reinforcement learning coursework on GitHub, refining RL agents and ensuring Python 3 compatibility, which signals continued technical curiosity and applied ML competence. Pragmatic and process-oriented, he excels at aligning design, engineering and business stakeholders to deliver measurable product impact.
10 years of coding experience
13 years of employment as a software developer
Master's degree, Informatics and Telecommunications, Master's degree, Informatics and Telecommunications at MIEM HSE, Moscow, Russia1205
Русский, English, Serbian
Github Skills (9)
deep-reinforcement-learning10
pytorch10
python10
reinforcement-learning10
machine-learning9
courses-resource8
deeplearning-ai7
deep-learning7
keras5
Programming languages (8)
Github contributions (5)
yandexdataschool/Practical_RL
Mar 2018 - Apr 2018
A course in reinforcement learning in the wild
Role in this project:
ML Engineer
ML EngineerContributions:12 commits, 6 PRs in 1 month
Contributions summary:Alexey primarily contributes to reinforcement learning coursework, focusing on implementing and refining RL agents. They modify existing code to update agent parameters, ensuring Python 3 compatibility, and integrate key concepts such as entropy regularization and advantage calculation. Their contributions span across various aspects of the RL project, enhancing existing notebooks and ensuring code correctness.
pytorchgit-coursedeep-learningreinforcement-learningwild
kventinel/configs
Dec 2019 - Oct 2022
Contributions:68 pushes, 1 branch in 2 years 10 months
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