Катерина

KATERYNA KOZII
Junior Data Analyst
Phone: [відкрити контакти](див. вище в блоці «контактна інформація») Location: Odesa, Ukraine
Email: [відкрити контакти](див. вище в блоці «контактна інформація») LinkedIn: [відкрити контакти](див. вище в блоці «контактна інформація»)
Telegram: https://t.me/ckozii GitHub: https://github.com/KaterinaKozii
SUMMARY:
Junior Data Analyst with 10 years of engineering and leadership experience, applying analytical and
problem-solving skills to business and marketing data.
Experienced in working with large volumes of structured information, analyzing performance
indicators, and improving operational efficiency. Currently applying SQL, Python, Tableau, and
statistical methods to solve business problems through portfolio projects in marketing and
product analytics.
Particularly interested in marketing, product, and business analytics, where analytical thinking and
business understanding can drive measurable impact.
HARD SKILLS:
Data Analysis; Data Cleaning & Preprocessing; Exploratory Data Analysis (EDA); Statistical Analysis;
SQL Querying; Data Visualization; Cohort Analysis; Retention Analysis; A/B Testing; Business
Metrics Analysis; Data Interpretation; Reporting; Process Analysis; Dashboard Development

TOOLS:
Python: Pandas, NumPy, Matplotlib, Seaborn
SQL: PostgreSQL, BigQuery
Tableau / Looker Studio
Excel / Google Sheets
Jupyter Notebook
Git
GitHub

SOFT SKILLS:

Analytical Thinking; Cross-Functional Communication; Responsibility; Continuous Learning

PROJECT EXPERIENCE:

Marketing Campaign Performance Analysis | GitHub:
https://github.com/KaterinaKozii/marketing-campaign-performance-analysis
Technologies: Jupyter Notebook, Pandas, NumPy, Matplotlib, Seaborn
Description:
Analyzed Facebook Ads campaign performance to evaluate marketing efficiency, profitability, and
budget allocation.
Tasks:
Cleaned and prepared advertising data
Calculated ROMI and analyzed daily advertising performance
Compared campaigns by spend, value, and ROMI
Built visualizations to identify trends, outliers, and campaign stability
Analyzed correlations between spend, value, impressions, clicks, CTR, CPC, and ROMI
Result:
Identified the most profitable campaigns based on ROMI performance.
Found that high budget did not always mean high efficiency
Prepared data-driven recommendations for budget optimization and campaign scaling based
on ROMI performance.

A/B Test Plan for Weekly Subscription Conversion | GitHub:
https://github.com/KaterinaKozii/ab-test-weekly-subscription-conversion
Technologies: Python, A/B Testing, Statistical Planning, MDE, Sample Size Calculation
Description:
Planned an A/B test for a mobile app weekly subscription screen to evaluate whether a “50%
discount” framing can increase install-to-purchase conversion.
Tasks:
Defined H0/H1 hypotheses
Selected primary and secondary metrics
Calculated baseline conversion, MDE, required sample size and test duration
Prepared business recommendations and a decision framework based on expected
conversion, ARPU, refund rate, and churn impact.
Result:
Recommended a 50/50 randomized A/B test with 51,890 total installs
Estimated required sample size: 25,945 installs per group
Defined 28-day test duration and success criteria for product decision-making
WORK EXPERIENCE:
Head of Department | DANLIN
October 2024 – December 2025
• Managed department operations and coordinated cross-functional workflows
• Worked with project budgets, performance indicators, and operational reporting to support
management decisions.
• Monitored project timelines, budgets, and resource allocation
• Analyzed project performance indicators and identified process bottlenecks
• Prepared reports and supported management decision-making using project data
• Improved workflow efficiency and communication between teams
Key Achievements:
• Improved workflow efficiency by optimizing project coordination and reducing delays across
multiple construction projects.
• Successfully coordinated multiple projects simultaneously while maintaining quality standards

Civil Engineer | DANLIN
January 2015 – October 2024
• Worked with technical documentation, project budgets, schedules, estimates, and performance
indicators to support planning and decision-making
• Analyzed project requirements and monitored execution progress
• Maintained data accuracy and compliance with industry standards
• Collaborated with contractors, clients, and project teams
Key Achievements:
• Contributed to successful delivery of construction projects
• Maintained high accuracy in project documentation and reporting
EDUCATION:
IT School GoIT
Data Analytics | 2026
Odesa State Academy of Civil Engineering and Architecture
Bachelor’s degree in Construction | 2011 - 2015

LANGUAGES:

English — Intermediate
Ukrainian — Native
Russian — Native