- NLP Tech Lead at Sber AI Π‘enter
- Master Student at CMC MSU
Field of interests: NLP, RL, Graphs, MLOps
- Languages: Β Python
- DS/ML/DL: Β Β NumPy, SciPy, Pandas, Scikit-Learn, PyTorch
- RDBMS: β Β Β MySQL, PostgreSQL, Oracle, MSSQL
- Big Data: βΒ Hadoop, HDFS, MapReduce, Hive, Spark
- DevOps:β βΒ Linux, Git, Docker, CI
Job Position | Company | Field | Work Period |
---|---|---|---|
NLP Tech Lead | Sber AI Π‘enter | NLP, MLOps, Mentoring | 01.04.2021 β until now |
Senior NLP Engineer | Tinkoff AI Lab | Virtual Assistant "Oleg" | 01.02.2021 β 01.04.2021 |
Middle NLP Engineer | MTS AI Lab | NER with Pseudo-Labeling | 01.05.2020 β 01.02.2021 |
Junior Data Scientist | Sberbank | ML with Tabular Data, CV | 01.07.2018 β 01.05.2020 |
Research Assistant | Plekhanov RUE | Research in DS, ML, Big Data | 01.12.2018 β 01.01.2020 |
More about work experience in my LinkedIn
My solutions for Home Assignments for Machine Learning Job Interviews: link
- Masterβs degree in Applied Mathematics and Computer Science at Lomonosov Moscow State University (2019 - 2022)
- Coursework: "Prior knowledge layer for sequence tagging"
- Bachelor's degree in Applied Mathematics and Computer Science at Plekhanov Russian University of Economics (2015 - 2019)
- Diploma thesis: "Assessment of credit organizations borrowers' default rate"
- Calculus of Variations - bachelor project on solving the Calculus of Variations problems
More about education in my LinkedIn.
- QaNER - unofficial implementation of QaNER paper (NER via Question Answering)
- RLLib - reinforcement learning library
- MUSE as Service - REST API for sentence embedding using Multilingual Universal Sentence Encoder
- PyTorch NER - pipeline for training NER models using PyTorch
- Text Classification Baseline - pipeline for building text classification TF-IDF + LogReg baselines
- Graph-Based Clustering - clustering using graph connected components and spanning trees
- Web-Service for Sentence Embeddings @ Sberloga
- Git Hooks Is All You Need @ Sberloga
- How to start a career in DS @ REU Data Science Club
- Introduction to Machine Learning @ Coursera
- Supervised Learning @ Coursera
- Introduction to Deep Learning (with honors) @ Coursera
- Bayesian Methods for Machine Learning (with honors) @ Coursera
- Practical Reinforcement Learning (with honors) @ Coursera
- Introduction to Linux @ Stepik
- Version Control with Git @ Coursera
- Hadoop. System for processing large amounts of data @ Stepik
More certifications in my LinkedIn.
- IX International Scientific and Practical Conference named after A.I. Kitov "Information Technologies and Mathematical Methods in Economics and Management" (website and certificate)
- Deep and Machine Learning methods for document clustering and classification tutorial in frames of The XXIII International Scientific Conference of Young Scientists and Specialists (AYSS-2019) (website)
- Synthetic Health Data Hackathon 2020 Alzheimer's MRI Analysis
- Published 7 packages to PyPI
- Contributor to SciPy, Scikit-Learn, PyTorch
- Co-author of Quantum Machine Learning Community Course
- Open Data Science Best Contributor 2020
- Awesome GitHub Profile README (Category: Descriptive π)