Position: Data Scientist / Machine Learning Engineer
Category: Data Science
English level: fluent
Years of experience: 1.5


Machine Learning Engineer - 
 Developed machine learning models to predict currency rates using time-series analysis, boosting and ensemble algorithms.
 Customized hyperparameter tuning and weights adjustment methods; implemented risk management and backtesting using
Backtrader package; automated data acquisition from Interactive Brokers using TWS and ib_insynс package.
 Built a classification model for churn prediction with an AUC-ROC score of 0.988 and F1-score of 0.798; сonducted experiments to
handle imbalanced target distribution by creating synthetic data using CTGAN.

Research Assistant
 Submitted paper titled “Mechanical and thermal properties of BN doped graphene: Molecular Dynamics Simulation and
Machine Learning Analysis”.
 Implemented Support Vector Regressor to model physical properties of graphene based on its molecular structure reaching an
R-squared of 0.75, 0.86, 0.91 and 0.88 for four targets.
 Built a reverse optimization algorithm to predict 200-D molecular structure of graphene based on desired values of its 4 physical
properties using Genetic Algorithm in Python.

Data Scientist
 Developed regression and time-series models for 21 macroeconomic indicators of Kazakhstan.
 Performed data analysis, data visualization and feature engineering in Python and Power BI.
 Conducted statistical tests to validate linear regression and time-series assumptions; Created an analytical report.
Data driven methods into solving real-world challenges.