Юлія

YULIIA PODOLIAN
Data Analyst
Groningen, Netherlands | [відкрити контакти](див. вище в блоці «контактна інформація») | [відкрити контакти](див. вище в блоці «контактна інформація»)
LinkedIn: [відкрити контакти](див. вище в блоці «контактна інформація») | GitHub: https://github.com/Julia1671

SUMMARY
Junior Data Analyst with a background in mathematics and computer science.
Skilled in SQL, Power BI, and Tableau, with hands-on experience building dashboards and
analyzing real-world datasets. Completed an independent project analyzing Formula 1 performance
data, where I developed interactive dashboards and uncovered patterns between qualifying results
and race outcomes. Focused on transforming raw data into clear insights that support better
decision-making.

SKILLS
HARD SKILLS
Data Analysis, Exploratory Data Analysis (EDA), Data Cleaning & Data Validation, Statistical
Analysis, Hypothesis Testing, A/B Testing, Data Visualization, Data Storytelling, Product Analytics,
Business Metrics Analysis (Conversion Rate, ARPU, LTV, Retention, Churn), KPI Analysis, Cohort
Analysis
TOOLS
SQL (advanced queries, joins, window functions), Python (Pandas, NumPy), Data Visualization
(Tableau, Power BI, Looker Studio), Google Analytics 4, BigQuery, Excel, Google Sheets, Matplotlib,
Seaborn, Jupyter Notebook
SOFT SKILLS
Analytical Thinking, Problem Solving, Attention to Detail, Communication, Adaptability

PROJECTS
Formula 1 Performance Analysis (SQL, Power BI)
https://github.com/Julia1671/formula1-data-analysis
Technologies: SQL, Power BI
Analyzed Formula 1 race data to identify key factors influencing performance
Cleaned and transformed raw data using SQL (joins, aggregations, data preparation)
Built an interactive Power BI dashboard to explore driver performance, starting positions,
and pit stop strategies
Analyzed relationships between starting position, position changes, and total points
Created visual insights to support data-driven understanding of race outcomes

Revenue Metrics Dashboard (SQL, Tableau)
https://public.tableau.com/views/Finalproject_17706471258730/RevenueMetrics2022?:language=e
n-US&:sid=&:redirect=auth&:display_count=n&:origin=viz_share_link
Technologies: SQL (PostgreSQL), Tableau
Analyzed subscription-based product metrics including MRR, ARPPU, churn rate, and user
growth
Processed and aggregated raw data using SQL to prepare datasets for analysis
Built an interactive Tableau dashboard to track revenue trends and user behavior
Enabled segmentation by user attributes (e.g., language, age group) for deeper analysis
Identified key drivers of revenue changes and user retention
Sales & Shipping Analytics Dashboard (Tableau)
https://public.tableau.com/shared/W4W2Z5S4P?:display_count=n&:origin=viz_share_link
Technologies: Tableau
Developed an interactive dashboard to analyze sales performance, profitability, and
shipping efficiency
Built time-series analysis of sales and profit trends
Created visualizations for product-level profitability and category performance
Analyzed delivery time and shipping methods to identify operational patterns
Used filters and interactive elements to enable dynamic data exploration

LANGUAGES
English — Upper-intermediate
Ukrainian — Native

EDUCATION
IT School GoIT
Data Analytics Program
2025 – 2026

Taras Shevchenko National University of Kyiv
Master’s Degree — Psychology
2024 – 2025
Master’s Degree — Public Management and Administration
2023 – 2024
Bachelor’s Degree — Mathematics and Computer Science
2019 – 2023