Yurii Yosypiv
Dev Team Lead at BCD TripTech
Lviv, Lviv Oblast, Ukraine
Summary
🤩
Rockstar🎓
Top SchoolYurii Yosypiv is a Dev Team Lead and software engineer from Lviv with 4 years of professional experience building backend and full-stack systems across startups and established firms. He brings practical leadership from roles at BCD TripTech and earlier stints at SoftServe and niche analytics teams, where he focused on workflow optimization, architecture improvements, and mentoring junior engineers. Comfortable in Python microservices and asynchronous frameworks, he has shipped production-ready platforms for financial valuation and media monitoring, emphasizing performance by delegating long-running tasks to dedicated services. As an open-source contributor to Deepchecks, Yurii has hands-on ML validation experience—adding checks, tests and refactors that improve model and data quality. He values well-managed workflows and team wellbeing, believing urgencies should be timeboxed so teams can focus on what matters most. Colleagues find him easy to collaborate with and effective at turning complex requirements into maintainable solutions.
4 years of coding experience
3 years of employment as a software developer
Igor Sikorsky Kyiv Polytechnic Institute
Stackoverflow
53reputation
10kreached
0answers
2questions
Github Skills (13)
pandas10
eval10
data-validation10
python10
evaluation10
testing9
machine-learning9
aggregation-framework6
python-docx6
docx6
openxml6
mongodb6
mongoengine6
Programming languages (1)
Github contributions (4)
deepchecks/deepchecks
Nov 2021 - Jan 2023
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
Role in this project:
ML Engineer
ML EngineerContributions:341 reviews, 311 commits, 199 PRs in 1 year 2 months
Contributions summary:Yurii contributed to the Deepchecks project by implementing and adding conditions to existing checks. They were responsible for refactoring existing checks, added tests, and fixed bugs related to the checks' functionality. They worked on adding new conditions to the 'RareFormatDetection', 'TrainValidationDifferenceOverfit', 'SingleFeatureContributionTrainTest', and 'SingleFeatureContribution' checks, demonstrating an understanding of data validation and model evaluation techniques for machine learning models. Furthermore, the user contributed to the enhancement of existing checks by removing redundant params and comments, which shows an ability to maintain and improve software quality in the repository.
ml-modelspythonjupyter-notebookdata-modelsmodel-monitoring
yromanyshyn/tutorial-template
Dec 2021 - Dec 2021
Template for the Read the Docs tutorial
Contributions:3 releases, 2 pushes, 3 tags in 1 day
templateread-the-docs
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