Микита

Bc. Mykyta Karunyk
[відкрити контакти](див. вище в блоці «контактна інформація») [відкрити контакти](див. вище в блоці «контактна інформація») Brno, Czech Republic

Profile
Data Analyst / Junior Data Scientist with a strong quantitative background in mathematics,
econometrics, and applied data analysis. Currently pursuing a Master’s degree in Mathemati-
cal and Statistical Methods in Economics at Masaryk University. Experienced in SQL, Python,
and exploratory data analysis through academic and project-based work. Interested in pre-
dictive modeling, risk-related analytics, and translating analytical findings into clear business
conclusions.

Technical Skills
Programming and Querying: Python, SQL (PostgreSQL), R
Python Libraries: pandas, NumPy, scikit-learn, matplotlib
Data Analysis: exploratory data analysis, data cleaning, feature analysis, descriptive statis-
tics, data validation, model evaluation
Databases and Data Workflows: SQL querying, joins, aggregations, structured reporting,
working with relational data
Machine Learning: regression, classification basics, model comparison, introductory predic-
tive modeling
Other Tools: MS Excel (advanced), Git, Power BI, REST API basics, AI tools for analytical
and research workflows

Selected Projects
Traffic Flow Forecasting (Bachelor Thesis)
Built multi-horizon forecasting models (h = 1–24) using SARIMA/SARIMAX on real-world
traffic data from the UTD-19 dataset.

• Performed exploratory analysis and preprocessing of large hourly time-series datasets from
urban traffic sensors
• Implemented data cleaning, missing-value handling, and model preparation workflows
• Built and compared forecasting models using quantitative evaluation metrics
• Interpreted model outputs and summarized results in a structured analytical form

Consumer Behavior Prediction (Econometrics Project)
Developed regression-based models to analyze factors associated with purchasing decisions.

• Applied OLS and diagnostic testing to structured economic data
• Evaluated model assumptions, coefficient significance, and overall model performance
• Translated statistical results into practical analytical conclusions

Dashboard Development (Power BI)
Designed interactive dashboards for monitoring and visualizing economic indicators.

• Prepared and transformed data for reporting and dashboarding
• Built KPI-oriented dashboards to support structured interpretation of data

1
Credit Card Customer Clustering using Machine Learning Methods
Applied unsupervised machine learning methods to segment credit card customers based on
behavioral and financial usage patterns.

• Performed data cleaning, preprocessing, and exploratory data analysis on structured cus-
tomer data
• Used Python libraries such as pandas, NumPy, and scikit-learn for clustering workflows
• Analyzed customer groups based on spending, balance, cash advance, and usage frequency
variables
• Interpreted clustering results from a business perspective and identified meaningful customer
segments

Planar Data Classification Models (Neural Networks)
Built and evaluated neural-network-based classification models on planar datasets as part of
machine learning training.

• Implemented and tested classification models in Python
• Compared model behavior and decision boundaries across different approaches
• Worked with feature spaces, classification logic, and model performance evaluation
• Strengthened practical understanding of supervised machine learning workflows

Regression Models: Estimation of Production Functions of Different Countries’
Economies
Estimated and compared regression-based production function models for selected countries
using macroeconomic data.

• Applied econometric modeling techniques to analyze relationships between output and pro-
duction inputs
• Performed parameter estimation, model comparison, and interpretation of results
• Worked with structured economic datasets and statistical inference
• Summarized findings in a clear analytical form

Education
Masaryk University, Brno
Bachelor’s Degree in Mathematics (Minor in Economics)
Graduated: 2026
Relevant coursework:

• Data Analysis and Visualization
• Probability and Statistics
• Econometrics
• Databases and Information Systems
• Machine Learning

Work Experience
Masaryk University – Faculty of Informatics, Brno
Teaching Assistant / Teaching Support September 2025 – February 2026

• Supported course delivery during labs and consultations
• Reviewed assignments and provided structured feedback according to course requirements
• Assisted with the preparation and organization of course materials and documentation

2
 • Communicated technical concepts clearly and worked collaboratively with students and in-
structors

Additional Training
Research Data Management and Sharing
University of North Carolina at Chapel Hill (online course)
A Starter’s Guide to Open Science
Erasmus University Rotterdam (online course)
Neural Networks and Deep Learning
DeepLearning.AI (online course)

Languages
English – C1
Czech – C1
Ukrainian, Russian – native

3