Володимир

Volodymyr Vitkovskyi
Data Scientist

WORK EXPERIENCE
[відкрити контакти](див. вище в блоці «контактна інформація»)
Data Scientist
[відкрити контакти](див. вище в блоці «контактна інформація»)
PrivatBank
07/2023 - 08/2025, Kyiv, Ukraine
Key Responsibilities:
Kyiv, Ukraine Developed and implemented ML models for credit scoring.
Performed model validation, monitoring, and ongoing support.
[відкрити контакти](див. вище в блоці «контактна інформація») Conducted data analysis and feature engineering.
volodymyr
Developed and optimized complex SQL queries.
Created data visualizations for analysis and reporting.
github.com/Vvold Developed and explored ML model interpretability solutions.
Communicated and answered questions about developed ML models.
SKILLS
Python SQL
EDUCATION
ML Scikit-learn Master's degree in Computer Engineering
National Technical University of Ukraine “Igor Sikorsky Kyiv
Pandas Numpy Polytechnic Institute”
09/2023 - 12/2024,
Keras Matplotlib
Bachelor`s degree in Computer Engineering
Plotly Seaborn National Technical University of Ukraine “Igor Sikorsky Kyiv
Polytechnic Institute”
Git Docker 09/2019 - 06/2023,

Linux OOP
PERSONAL PROJECTS
ORM Statistics
Recognition of Tree Leaves
Classified photos of leaves to identify which tree species they belong to using neural networks.
Math A/B testing Created a Flask app that allows interaction with the neural network.
Technology stack: Python, Flask, keras, numpy, data preprocessing, matplotlib, git
NoSQL Link: https://github.com/Vvold/Recognition-of-Tree-Leaves

Used Cars Price Prediction
Predicted car prices using a dataset of vehicle characteristics. Achieved optimal performance
based on MSE. Built a pipeline.
LANGUAGES Technology stack: Python, XGBoost, pandas, numpy, sklearn, Pipeline, matplotlib, seaborn, git
Link: https://github.com/Vvold/Cars-Price-Prediction-XGBoost
English (intermediate)
Ukrainian (native) Store Sales - Time Series Forecasting
Conducted research on sales data from Favorita stores in Ecuador. Forecasted product sales
using an LSTM-based time series model.
Technology stack: Python, LSTM, keras, pandas, numpy, time series forecasting, plotly, git
Link: https://github.com/Vvold/Store-Sales-Time-Series-Forecasting