Іванна

CHEPARA IVANNA
Data Analyst

[открыть контакты](см. выше в блоке «контактная информация») https://t.me/Ivannaach [открыть контакты](см. выше в блоке «контактная информация») Ivano-Frankivsk, Ukraine

ABOUT ME
Junior Data Analyst actively learning and applying knowledge through practical projects. Skilled in working
with data, preparing tables, and making initial analytical insights. Motivated to grow and quickly learn new
skills within a team.

EDUCATION
IT SCHOOL “GOIT” 2026
Data Analyst
PRECARPATHIAN NATIONAL UNIVERSITY NAMED AFTER VASYL STEFANYK 2024-Present
Bachelor’s in Marketing, 2nd Year

HARD SKILL
SQL (basic queries, data extraction) Python (Pandas, NumPy,Matplotlib, Seaborn )
Excel (formulas, sorting, filtering, tables) Basic Statistics (mean, median, correlation)
Google Sheets (data processing and visualization) Exploratory Data Analysis (EDA)

SOOFT SKILL
Willingness to learn and develop Teamwork
Organization Adaptability

TOOLS
SQL Python Seaborn
Excel Pandas PyCharm
Google Sheets NumPy Jupyter Notebook

PROJECT EXPERIENCE
Streaming Services Analytics
https://docs.google.com/spreadsheets/d/1iv_Z9l7yBM5Da4OEp2m3cNgvIRCtANqDy49vM-V2Rqc/edit?
usp=sharing
Technologies: Google Sheets, SQL, Pivot Tables, Charts, Dashboards
Description & Idea:
The project focused on analyzing streaming data to understand user preferences, popular movie genres, and viewing
patterns by country.
Tasks:
• Cleaned and prepared data for analysis
• Analyzed genres, subscription types, and viewing patterns by country
• Created pivot tables and charts
• Performed SQL queries
• Built a dashboard to visualize insights
Result:
Delivered an interactive dashboard and visual reports showing user behavior, popular genres, and subscription trends,
demonstrating skills in data analysis and visualization.
Global Developer Trends & Compensation Analysis

(Stack Overflow Developer Survey 2025)**
• Technologies: Python, Pandas, Jupyter Notebook / Google Colab, Tableau / Looker Studio
• Description: Analysis of the Stack Overflow Developer Survey 2025 dataset (49,000+ respondents from 177 countries).
• Idea: Identify key trends in programming technologies, learning paths, and developer compensation.
• Tasks: Analyzed Python adoption, learning methods, country-level compensation (mean and median), education of top 5 highest-
paid respondents, and industries of high-paid remote workers.
• Outcome: Revealed global Python usage trends, compensation differences across countries, and leading industries among high-
income remote professionals, presented through analytical tables and BI dashboards.

LANGUAGES
Ukrainian — Native
English — Beginner (currently learning, willing to improve for work)