Nataliia

Email: [відкрити контакти](див. вище в блоці «контактна інформація»)
Synytsia Nataliia Telegram: @nata_synytsia
Junior Data Analyst GitHub: https://github.com/sevenN0007
Location: Ukraine Open to: Hybrid/ Remote

Summary:
Junior Data Analyst with a Bachelor's degree in Applied Mathematics and Science of Data
from the NTUU KPI. Strong foundation in statistics, hypothesis testing, and exploratory
data analysis. Experienced in working with real-world datasets and processing data using
Python, R, and SQL.

Technical skills:
Programming:
● Python (pandas, NumPy, SciPy, Matplotlib)
● R (statistical analysis, bootstrap method, visualization)
● SQL (SELECT, JOIN, GROUP BY, HAVING, ORDER BY, subqueries)
● Excel/ Google Sheets (smart tables, pivot tables, vlookup)
● Tableau

Statistics & Data Analysis:
● Hypothesis testing (Z-test, t-test, Wald test)
● Confidence intervals (asymptotic, bootstrap)
● Exploratory Data Analysis (EDA)
● Data cleaning and preprocessing
● Data visualization and result interpretation
● Machine Learning: linear regression, basic classification, model evaluation
metrics

Academic projects:
● Built a weighted road network of Kyiv using OpenStreetMap (OSMnx) and
NetworkX, integrating Uber Movement travel time data. Calculated over 5 network
reliability metrics, including global efficiency and node centrality scores, and
developed interactive visualizations using Streamlit and Folium.
● Performed exploratory data analysis and statistical hypothesis testing on real-world
datasets using R (t-tests, F-tests, Z-tests, Wald test). Built bootstrap confidence
intervals for the mean and variance using the boot package; interpreted results and
created data visualizations.
● Developed multiple linear regression models to analyze 4 key factors influencing
movie ratings (budget, duration, number of votes, release season). Conducted model
diagnostics, assessed variable significance using p-values, interpreted model
performance using R² and translated findings into analytical insights.
● Solved optimization problems using linear programming and analyzed M/M/r/m
queueing systems to evaluate production planning, retail optimization, system
utilization, waiting times, and capacity constraints.
● Worked with 3 databases: relational (PostgreSQL, MySQL) and non-relational
(MongoDB), containerization (Docker), and message brokers (RabbitMQ) as part of
data processing and distributed systems.

Education:
National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic
Institute” (NTUU KPI)
Faculty of Applied Mathematics

Languages:
Ukrainian – Native
English – B1