Dmitry Chigarev
Software Engineer at Intel Corporation
Munich, Bavaria, Germany
Summary
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Rockstar🎓
Top SchoolDmitry Chigarev is a software engineer based in Munich with six years of experience building backend systems and data-focused tooling at Intel. He contributes to high-impact open-source data projects, notably implementing and hardening Series/DataFrame APIs in the widely used Modin library—adding features like .nunique() and .pivot() and fixing tricky categorical dtype bugs. Comfortable spanning data science and backend development, Dmitry has a proven track record of improving memory behavior and aggregate operations in large-data workflows. A UNN computer science graduate, he pairs solid engineering at a major semiconductor firm with active contributions that help scale pandas workflows with minimal code changes.
6 years of coding experience
2 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at State University of Nizhni Novgorod named after N.I. Lobachevsky (UNN)
Stackoverflow
150reputation
2kreached
2answers
0questions
Github Skills (17)
python10
dataframes10
pandas10
dataframe10
data-structure9
performance-analytics9
performance-monitor9
performance-measurement9
performance-monitoring9
performance-analysis9
data-structures9
performance-tuning9
data-analysis8
testing8
data-science8
Programming languages (3)
Github contributions (5)
modin-project/modin
Apr 2020 - Jan 2023
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:1 release, 2474 reviews, 160 commits in 2 years 9 months
Contributions summary:Dmitry Chigarev contributed to the implementation and refinement of the Series and DataFrame APIs within the Modin library, specifically focusing on functionalities related to memory usage, unique value counts, and mathematical operations. He addressed and fixed a variety of issues related to data types, notably resolving problems with categorical dtypes in operations like `ravel` and `drop_duplicates`. Furthermore, he expanded the library's capabilities by introducing a range of new features, including `.nunique()` and `.pivot()` methods.
analyticspythonline-of-codedata-sciencedataframe
dchigarev/graph-compiler
May 2024 - Dec 2024
Contributions:105 pushes, 32 branches in 7 months
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