Alexey Belkov

Data Scientist

https://talent.gravityer.com/alexey-belkov

MIPT masters Applied Mathematics & Physics student and Yandex School of Data Analysis alumni

Teza Technologies LLC

Key Strengths

Strong background in machine learning and deep learning, evidenced by projects like 'MedQ', 'nekograd', and 'YSDA-CPU-inference'.
Proficiency in Python and C++ for data science and high-performance computing, as seen in 'imops', 'parinterp', and 'YSDA-CPU-inference'.
Experience with neural network quantization and optimization for CPU inference, directly relevant to data scientist roles involving model deployment.
Exposure to compiler technologies (LLVM) and CUDA, indicating a deep technical curiosity and ability to work at lower levels of the stack.
Active personal project contributions demonstrate initiative and continuous learning in relevant technical areas.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's personal projects show a strong interest in advanced topics within machine learning, optimization, and low-level computing, which aligns well with a research-oriented or performance-critical data scientist role. The diversity of projects, from RL to quantization and compilers, suggests a broad technical curiosity. However, without information on team collaboration or work attitude, a full cultural fit assessment is limited. The current role as 'Data Scientist' at Teza Technologies LLC aligns with the target role.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are concise, but no direct communication or collaboration examples are provided. Psychometric test results are not available.

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Projects

cuda-samples

December 12, 2025 – December 12, 2025

cuda-samples — GitHub repository

View Project

llvm-gym

December 9, 2025 – December 9, 2025

llvm-gym — GitHub repository

View Project

cats-compiler

December 29, 2024 – December 24, 2025

LLVM based compiler for CatBoost trees

View Project

rl-vcmi

July 31, 2024 – July 31, 2024

rl-vcmi — GitHub repository

View Project

micrograd

July 15, 2024 – December 3, 2024

micrograd — GitHub repository

View Project

MedQ

May 17, 2024 – May 17, 2024

Implementation of MedQ: Lossless ultra-low-bit neural network quantization for medical image segmentation

View Project

YSDA-CPU-inference

October 5, 2023 – December 29, 2023

Quantized inference on CPU (int8 / int4 / mixed precision )

View Project

parinterp

July 28, 2023 – December 20, 2023

Python binding of 2D delaunay triangulation and parallel linear interpolation

View Project

nekograd

November 17, 2022 – June 3, 2023

PyTorch-Lightning wrapped in some shit code

View Project

imops

August 10, 2022 – Present

Efficient parallelizable algorithms for multidimensional arrays to speed up your data pipelines

View Project

Key Strengths

Strong background in machine learning and deep learning, evidenced by projects like 'MedQ', 'nekograd', and 'YSDA-CPU-inference'.
Proficiency in Python and C++ for data science and high-performance computing, as seen in 'imops', 'parinterp', and 'YSDA-CPU-inference'.
Experience with neural network quantization and optimization for CPU inference, directly relevant to data scientist roles involving model deployment.
Exposure to compiler technologies (LLVM) and CUDA, indicating a deep technical curiosity and ability to work at lower levels of the stack.
Active personal project contributions demonstrate initiative and continuous learning in relevant technical areas.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Alexey Belkov

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit