Особисті дані приховані

Tetiana Reznychenko
ï tetiana-reznychenko | € Google Scholar | # [відкрити контакти](див. вище в блоці «контактна інформація») | H [відкрити контакти](див. вище в блоці «контактна інформація»)

Summary
Has 3+ years of experience in data science, 2+ years of commercial experience. Over 5 years of program-
ming experience, including 2+ years as a database developer and 3+ years involving analysis in Python.
Designed custom algorithms for survey data, which enhanced model performance by 10%. Led an end-to-
end analytical project. Finished 4+ projects. Has 5+ publications. Holds a Master’s degree in Applied
Mathematics.

Skills
Tech tools Python, SQL, Git, CI/CD, AWS
Libraries Scikit-learn, XGBoost, AutoGluon, Pandas, Numpy, Scipy, Statsmodels
Visualization: Matplotlib, Seaborn, Plotly, Tableau
Areas of expertise: Data Analysis, Feature Engineering, AI, ML/predictive modeling
Languages English (Advanced), Ukrainian (Native), Russian (Native), Czech (Elementary)
Soft skills Problem-solver with analytical mindset, team collaboration, detail-oriented, mentor-
ing experience

Work Experience
Czech Technical University Prague, Czech Republic
Data Scientist & Researcher Feb 2022 - Present
Leading technical university in the Czech Republic, actively involved in national and EU-funded research
initiatives. Contributed to government-funded research projects, focusing on intelligent transport systems
and smart cities.
– Designed and implemented predictive models for smart city systems and traffic injury forecasting using
algorithms such as Random Forest, Logistic Regression, and Gradient Boosting, contributing to safer
and more efficient urban mobility systems.
– Improved model performance by 22% through advanced feature engineering (PCA, feature selection
techniques), model tuning (Random Search), and systematic model comparison using cross-validation.
– Engineered and evaluated custom algorithms for survey data.
– Applied statistical and mathematical techniques including hypothesis testing (Z-test), distribution fit-
ting, and regression analysis for deep data insight extraction.
– Created reproducible data analysis pipelines (Scikit-learn, Pipelines) and visualizations using Python
libraries: Matplotlib, Seaborn, Plotly.
– Mentored students in data analysis and applied mathematics.
Fozzy Group Kyiv, Ukraine
Data Analyst Dec 2021 - Feb 2022
Fozzy Group is one of the largest industrial and retail groups in Ukraine and a leading national retailer,
operating over 700 outlets across the country. In addition to its retail chains, the Group’s business interests
include food production, banking, and restaurant services.
– Maintained and managed relational databases: cleaned, updated, and validated large datasets to ensure
data quality and consistency.
– Wrote and optimized complex SQL queries for data extraction, transformation, and reporting to support
business analysis and product tracking.
– Collaborated with analysts and data engineers to ensure proper data flow, troubleshoot data issues,
and support ongoing data infrastructure improvements.
Insurance company “Misto” Vinnytsia, Ukraine
Database Developer Feb 2020 - Nov 2021
IC ”Misto” is a public insurance company in Ukraine that provides health and life insurance services.
– Designed and implemented structural changes in the database to support the launch of a new insurance
product.
– Performed routine database administration tasks including data updates, backups, optimization, and
troubleshooting to maintain high system availability and data integrity.
– Collaborated closely with technical teams and cross-functional stakeholders to gather requirements,
implement solutions, and ensure alignment between database architecture and business needs.

University of Alberta Camrose, Canada
Researcher Jun 2018 - Sep 2018
One of Canada’s leading research-intensive universities, recognized globally for excellence in teaching,
research, and innovation.
– Cleaned and preprocessed datasets using Python, handling duplicates, missing values, and normaliza-
tion. Used Pandas and NumPy for data manipulation and analysis.
– Created visualizations with Matplotlib and Seaborn to support research insights.

Projects
Transport digital twin European
The aim of the project is to make more efficient use of multimodal transport information for the purpose
of verifying proposals and new technologies. A digital model of a real transport environment using current
traffic data will be created
Task: preprocessed and cleaned raw data; wrote Python scripts to automate data validation,
formatting, and transformation.

Education
2022 — Present PhD at Czech Technical University
2019 — 2020 Master’s Degree in Applied Mathematics at Vasyl’ Stus Donetsk National University
2015 — 2019 Bachelor’s Degree in Applied Mathematics at Vasyl’ Stus Donetsk National University