Senior Data Scientist at Wiredhut. My skills are related to the spatio-temporal data analysis. But I also do the typical Data Science tasks :)

I have experience in backend development, can do simple one-page websites (fronted skills). Well skilled in architecture design and programming in general (patterns, OOP, SOLID, TDD, git) and ML systems in particular. My main focus is a "combination of machine learning and backend development" using Python. Experienced in R&D (have more than 30 publications).

My tech stack: Python, FastAPI, scikit-learn, networkx, PyTorch, MLFlow, Dask, SQLAlchemy, alembic, docker, PostgreSQL, MongoDB, GDAL, QGIS, LaTex etc.

Some open-source developments in which I have been or am involved:

• AutoML framework FEDOT
• Time series benchmark pytsbe
• ETL (Extract, Transform, Load) library wiredflow
• Library for spatial data fusion and processing for real estate objects estaty
• Module for filling gaps in matrices (applied mostly for remote sensing data) based on machine learning and spatial relations SSGP-toolbox
• QGIS plugin for river stream ordering (or any vector linear system) Lines Ranking

I write, along with my colleagues, posts on Towards Data Science, Medium and Habr.

Towards Data Science:

• Stream Ordering: How And Why a Geo-Scientist Sometimes Needed to Rank Rivers on a Map (eng)
• A Data Science Course Project About Crop Yield and Price Prediction I’m Still Not Ashamed Of (eng)
• Almost Everything You Want to Know About Partition Size of Dask Dataframes (eng)
• Proximity Analysis to Find the Nearest Bar Using Python (eng)
• Combining Open Street Map and Landsat open data to verify areas of green zones (eng)
• What to Do If a Time Series Is Growing (But Not in Length) (eng) - NSS Lab post
• Hyperparameters Tuning for Machine Learning Model Ensembles (eng) - NSS Lab post
• Clean AutoML for “Dirty” Data: How and why to automate preprocessing of tables in machine learning (eng) - NSS Lab post
• One more approach to optimize neural networks (eng)
• Winning a Flood-Forecasting Hackathon with Hydrology and AutoML (eng) - NSS Lab post
• AutoML for time series: advanced approaches with FEDOT framework (eng) - NSS Lab post
• AutoML for time series: definitely a good idea (eng) - NSS Lab post

Medium:

• The Algorithm for Ranking the Segments of the River Network for Geographic Information Analysis Based on Graphs (eng)

Habr:

• Data Scientist in Helsinki. Мое небольшое исследование про поиск работы в Финляндии в 2024 году (rus)
• “Ну и долго мне ещё до магазина?” Или пара слов о геоинформационном анализе с помощью Python (rus)
• Объединение открытых данных Open Street Map и Landsat для уточнения площадей зеленых зон (rus)
• Что делать, если твой временной ряд растёт вширь (rus) - NSS Lab post
• Про настройку гиперпараметров ансамблей моделей машинного обучения (rus) - NSS Lab post
• Чистый AutoML для “грязных” данных: как и зачем автоматизировать предобработку таблиц в машинном обучении (rus) - NSS Lab post
• Как мы “повернули реки вспять” на Emergency DataHack 2021, объединив гидрологию и AutoML (rus) - NSS Lab post
• Прогнозирование временных рядов с помощью AutoML (rus) - NSS Lab post
• Алгоритм ранжирования сегментов речной сети с использованием графов для геоинформационного анализа (rus)

My accounts on other platforms: scholar.google, kaggle, drivendata