Особисті дані приховані

Yurii
DATA ANALYST

PROFESSIONAL SUMMARY
Data Analyst with a strong background in Economics and hands-on experience in using statistical methods
and data visualization. Skilled in Python, SQL, and Power BI. Passionate about transforming raw data into
clear, actionable insights that generate business profit and minimize risks in times of uncertainty. Seeking
remote-only opportunities.

Telegram: Email: City: Kyiv
t.me/Alt_2203 [відкрити контакти](див. вище в блоці «контактна інформація») GitHub: link

EDUCATION
Bachelor of Science in finance and credit | 2012-2016
National Transport University, Kyiv

EXPERIENCE
Collections Specialist | 8+ years of experience
Leading Ukrainian fintech companies (TOP-3 microcredit market)
Analyzed overdue portfolios and customer risk patterns, segmentation of customers according to
their financial capabilities
Conducted open-source research and data verification across multiple platforms
Negotiated repayment and restructuring agreements with clients
Worked with CRM systems to track and report on portfolio performance

Lead Generation Manager
International crypto exchanges
Researched and evaluated crypto projects across multiple platforms including exchanges, news
sources, and blockchain explorers to identify listing opportunities
Conducted due diligence on token projects to assess legitimacy, market potential, and fraud risk
(anti-scam screening)
Communicated with project representatives and token teams to negotiate listing agreements
Monitored industry news and competitor exchanges to identify emerging projects at early stages

SKILLS
B2 level in spoken English (Certificate (C1))
Power BI
SQL, PostgreSQL
BigQuery
Python
Statistical analysis
Google Sheets/Excel
Generative AI Tools (ChatGPT, Claude, Gemini)

PORTFOLIO
Salary Comparison Analysis (Bulgaria vs Ukraine) (github) (Power BI presentation)
A comparison of official data and data collected from job sites
Tech Stack: Python (Pandas, Pingouin, Playwright, BeautifulSoup), Google Sheets, Power BI.
 Developed a web scraping pipeline using Playwright to extract real-time vacancy data from major
job portals; integrated diverse datasets from Ukrstat, NSI Bulgaria, World Bank, and Numbeo.
Conducted hypothesis testing using Kruskal-Wallis and Mann-Whitney U tests; applied
log-linear regression to control for occupations and utilized Bootstrapping for robust result
validation.
Calculated real income differences adjusted for Cost of Living (CoL)

Test Date Bias in Ukraine’s 2024 GACT: Multivariate Analysis of Cognitive Scores and Key
Predictors
(github)
Analysis of the results of the largest cognitive assessment in Ukraine’s history
Tech Stack: Python (Pandas, Statsmodels, Seaborn), Advanced Statistics (LMM)
Analyzed large-scale national datasets using ANOVA and Linear Mixed-Effects Models (LMM).
Evaluated systemic fairness and socio-economic impacts on cognitive test scores through
multivariate statistical diagnostics.
Identified why scores varied across test dates and analyzed key factors to help improve the
education system.

Analysis of sales at an international online bicycle shop (github) (Power BI presentation)
Analysis of an online shop’s revenue streams and the development of actionable marketing
recommendations
Tech Stack: Power BI, SQL(PostgreSQL)
Used SQL to clean and verify data quality. Calculated key business metrics like revenue and profit.
Identified the most promising regions and analyzed which product categories have the best profit
margins.
Developed a dashboard to support data-driven business decisions. Identified specific steps for a
store relaunch, including product combinations and priority user segments for advertising
campaigns