Position: Data Scientist
Category: Data Science
English level: upper
Years of experience: 1


Data Scientist with 2+ years of experience both commercial and non-commercial. Have experience and familiar with such parts of the machine learning process: EDA, preparing data, training neural networks, core DS models, time series forecasting, NLP, and deployment. Currently passing a TensorFlow developer specialization to improve my knowledge in DL field and TF skills and studying at university on Bachelor degree: Applied Mathematics specialization. 

Work experience:
1) Role: Data Scientist
Responsibilities:
Ridership modeling with two models LSTM Neural Network, XGBoost.
Development of LSTM Neural Network for time series dataset (with lag shifting approach) to predict ridership data. Usage of machine learning libraries such as TensorFlow, Keras. Providing prediction results using python library Matplotlib.
Development of XGBoost regression for time series dataset (with lag shifting approach and dummy variables+rolling values approach). Usage of machine learning libraries: scikit‑learn, xgboost. Providing prediction results: RMSE, MAPE and plotting forecasts for next 15, 30 and 60 days.

Tools: Jupyter Notebook, Google Colab, Python(TensorFlow, Keras, scikit-learn, pandas, numpy, scipy, statsmodels).

2) Role: Data Analyst
Responsibilities:
Migration of data from onpremise databases to GCP and development of appropriate metrics which are comparing on-premise data to migrated in cloud. Development of Grafana dashboards describing data with developed metrics.

Tools:
BigQuery, PostgreSQL, Grafana, GCP

3) Several self-learning projects
ML project to undertake challenging problem, gain experience and improve my knowledge in DS field.