Data Scientist focused on applied ML, product analytics, and data engineering. I work at the intersection of data and decision-making — from building ML pipelines and running statistical experiments to forecasting business metrics and analyzing user behavior.
Currently exploring NER systems, time series forecasting, and turning messy real-world data into actionable insights.
| Project | Description | Stack |
|---|---|---|
| Strawberry-Duck | NER-based trending entity tracker from news sources (Yandex × ITMO) | Python · Docker · Airflow · PostgreSQL |
| AKI-Risk-Factors | Risk factor analysis for Acute Kidney Injury in post-surgical patients | Python · Scikit-learn · Statsmodels |
| US-Bike-Sharing-Analysis | B2C bike-sharing market analysis with unit economics & revenue forecasting | Python · Pandas · SciPy · Matplotlib |
| Data & ML |
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| Deep Learning |
|
| Data Engineering |
|
| Visualization |
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