Position: ML Engineer (Tech Lead)
Category: Data Science
English level: fluent
Years of experience: 5

- Boosting retention KPIs with churn prediction ML model with high AUC; 
- Transforming market strategy in time via causal inference analysis;
- Time series forecasts were within 5% MAPE for few months in the row; 
- Prototype of Kaldi speech recognition system in Ukrainian language with low WER etc;
- Customary parallelized AutoML system with best data processing / engine selection and hyperaparameter tuning for time series and tabular data;
- Approximation of real-world business process in healthcare system with simulation on simpy and RL optimization of key actors decision making.
Relevant projects as Data Scientist (2017-2022):
- ML classification model on customer churn via decision trees and MLP;
- Cluster analysis on customers;
- Causal inference analysis to detect effects of market interventions on trend change;
- Forecasting time series revenue via ARIMA, LSTM and FBProphet; 
- Forecasting sales: hierarchical time series with zero-inflated data;
- Regression analysis and data visualization on customer satisfaction KPIs;
- Google Analytics automated reporting and integration with BI tools;
- Speech Recognition system in Ukrainian language with Kaldi framework;
- Speaker diarization for operator-client dialogue;
- Retraining Credit Scoring system;
- AutoML pipelines deployment: 1) DataProcessing / FeatureEngineering / FeatureSelection; 2) Engines: h2o, autogluon, autokeras, tpot, optuna 3) Back-end: elasticsearch / redis / celery
- AutoML customary Time Series Forecasting functionality with best engine selection and transformations;
- Creating Simulation environment and RL optimization: 1)TicketingSystem with multiple nodes; 2)Simpy-based; 3)UI and backend configuration.
- Synthetic Data Generation via Bayesian networks / GANs