Position: Data Scientist
Category: Data Science
English level: upper
Years of experience: 2.5


I worked as data scientist and performed tasks such as:
Time-series analysis of stock price movements:
 - building prediction models for intraday trading using machine learning algorithms (boosting models, logistic regression, etc.);
- creation of most indicators and oscillators existed in trading;
- automatic detection of support and resistance levels;
- building OHLC candlestick charts using bokeh;
Analysis of uses' behavior in social discovery company:
- research of the possibility of reducing chargeback rates using machine learning; 
- building predictive models for prediction revenue by users for individual traffic buying channels;
- research on the problem of users’ repurchase and building models for assessing this effect on revenue;
- building a map of transitions of users from various empirical states of a user's life for subsequent testing of hypotheses to improve the current;

Education: Masters' degree in applied mathematics.

Key technical skills:
- programming language: Python;
- visualization tools and libraries: Tableau, bokeh, plotly;
- Python's libraries: numpy, pandas, scipy;
- machine learning and deep learning: lightgbm, scikit-learn, Keras;
- databases and data warehouses: PostgreSQL, MySQL, BigQuery;
- cloud services: AWS;
- OS: Linux, Windows, MacOS;
- knowledge of probability theory and statistics, optimization methods;
Professional data science team, established processes, remote-friendly