Alexander Myskov
Software Engineer at Yandex
Almaty, Kazakhstan
Summary
🤩
Rockstar🎓
Top SchoolAlexander Myskov is a software engineer with six years of experience building data-focused backend systems and platform services, currently at Yandex in Almaty. He has a strong foundation in radio engineering (BSc/MSc and ongoing PhD studies) that informs his methodical approach to system design and performance tuning. Previously he developed Database-as-a-Service and S3-as-a-Service products at Tinkoff and worked on Modin at Intel, contributing core Series methods, statistical functions, tests and documentation to a high-impact open-source project that scales Pandas workflows. His background spans low-level RF hardware engineering to AI frameworks and cloud platform tooling, enabling him to navigate both infrastructure and data-science workloads. Colleagues rely on him for thoughtful refactors and pragmatic fixes that improve clarity and testability in complex codebases. He combines academic rigor with production experience, often bridging research ideas into deployable engineering solutions.
7 years of coding experience
10 years of employment as a software developer
PhD student Radio Engineering, PhD student Radio Engineering at State University of Nizhni Novgorod named after N.I. Lobachevsky (UNN)
Github Skills (8)
dataframes10
pandas10
python10
data-science10
dataframe10
pytest9
unit-test9
unit-testing9
Programming languages (4)
Github contributions (5)
modin-project/modin
May 2020 - Apr 2022
Modin: Scale your Pandas workflows by changing a single line of code
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:445 reviews, 96 commits, 84 PRs in 1 year 10 months
Contributions summary:Alexander implemented the `is_unique` method for the Series class, contributing to the functionality of the Modin library. The contributions included adding the `is_unique` method itself, adding testing capabilities and expanding the types available for Series methods, along with changes to the documentation, and refactoring efforts. Furthermore, the user contributed fixes related to the application of functions, the implementation of the `kurt` and `kurtosis` methods, and addressing review comments regarding the code's structure and clarity.
modinpandasdataframedistributeddatascience
amyskov/omniscripts
Dec 2019 - Mar 2022
Scripts to benchmark omniscidb
Contributions:326 pushes, 114 branches in 2 years 3 months
benchmarkbenchmarking
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