Роман

ROMAN RAD
Data Analyst

CONTACT INFO EDUCATION

[відкрити контакти](див. вище в блоці «контактна інформація») Lviv National University
[відкрити контакти](див. вище в блоці «контактна інформація») Mathematics
Linkedin
Mate academy
Telegram
remote Data Analyst Course
Certificate link

SKILLS
EXPERIENCE
Spreadsheets: Pivot Tables, Data Cleaning,
Visualization
SQL: Advanced Queries, Window Functions, Data Analyst at DotCode | September
Query Optimization, Common Table 2025 – January 2026
Expressions (CTE) Built and maintained data models in dbt (staging
and marts layers)
Python: Pandas, NumPy, Matplotlib, Seaborn,
Created interactive dashboards and visualizations
Exploratory Data Analysis (EDA) in Metabase
Tableau: Interactive Dashboards, Data
Storytelling, Publishing PORTFOLIO
Statistics: Sampling, Hypothesis Testing,
Correlation, Statistical Significance Python Project
A/B Testing: Planning, Analysis, Reporting link
Other Tools: Jupyter Notebooks, Excel, Git, I have worked in the role of Data Analyst. I performed
Dbt, Metabase, VS Code EDA. I was using different technologies and tools like
importing files from Google Drive, Jupyter Notebook, and
LANGUAGES
different Python libraries. Made a different exploring
English – Upper-Intermediate job.Built a lot of charts with seaborn and matplotlib. Also
Ukrainian – Native Speaker left comments and recommendations for results.

Analysis of Furniture Sales
PERSONAL INFO link
I was working in the role of Data Analyst. I have loaded
10,000+ played chess games data from BigQuery to a Python Jupyter Notebook. My
Chess player with First Category title tasks were completing EDA (Exploring Data Analysis).
(Ukrainian national ranking system) Making analysis using Python and its libraries
Active participant in chess tournaments Matplotlib, Seaborn, Numpy, Pandas, and Statistics.
A many-time chess tournament winner. Finding insights and giving recommendations.
Have a lot of medals and cups.
A/B Testing
PC strategy games and overall gaming
link
enthusiast
Project, where I performed A/B testing in Jupyter
Notebook, but before this, I cleaned them and grouped
them in Google Sheets. Also, I’ve built a dashboard
where we can define the statistical significance of
metrics appropriate to Test number (There are 4
different Tests, each containing A and B groups). I made
it using the Python Programming Language for finding
statistically significant results.