Анна

ANNA [open contact info](look above in the "contact info" section)
[open contact info](look above in the "contact info" section)
NAUMCHUK github.com/AnnaNaumchuk

Junior Data Analyst Lutsk, Ukraine

SUMMARY
Junior Data Analyst with an engineering background and a strong mathematical foundation. Hands-on experience in
transactional data processing, financial metric calculation, and conversion funnel analysis. Strong SQL skills (window
functions, multi-table JOINs, CTEs), Python for statistical modeling, and Tableau and Power BI for interactive
dashboards. Experienced in analyzing transaction flows, identifying revenue leakages, and building anomaly-tracking
reports.

KEY SKILLS

Query & programming SQL (window functions, CTEs, multi-table JOINs), Python
BI & spreadsheets Tableau, Power BI, Google Sheets
Analytics & methods A/B testing, statistics, price elasticity modeling (log-log regression), RFM segmentation,
K-Means, Random Forest
Tools Jira, Confluence, AI-assisted analytics

PORTFOLIO
Project 1: Data-Driven Retail & Promo Optimization (End-to-End Analytics)
Analyzed regional retail sales by processing transactional data with SQL, modeling price elasticity of demand (PED)
in Python, and building an interactive Tableau dashboard.
SQL Query | Python Notebook | Tableau Dashboard
Project 2: Amazon Sales & Customer Insights Dashboard (Tableau)
Designed an e-commerce dashboard analyzing ₹1,118M in total revenue, seasonal category demand heatmaps,
customer repeat rate (81.4%), and return metrics.
Tableau Dashboard
Project 3: End-to-End A/B Testing & Conversion Funnel Optimization (Python)
Conducted statistical hypothesis testing and conversion funnel analysis across global product experiments to
evaluate user journey changes.
Google Colab Notebook
Project 4: Comprehensive Sales & Profit Performance Report (Google Sheets)
Analyzed sales and profit data across Europe and Asia (2010–2017), including ABC analysis, regional performance,
and delivery times, presented in an interactive dashboard.
Google Sheets Analysis
Project 5: E-commerce Customer Segmentation & Return Risk Analysis
Analyzed e-commerce sales performance, customer behavior, profitability, and return risk using RFM customer
segmentation, K-Means clustering, and Random Forest modeling. An interactive Power BI dashboard presents key
KPIs, customer segments, profitability insights, and business findings.
GitHub | Power BI

WORK EXPERIENCE
Freelance Data Analyst April – August 2026
• Wrote optimized SQL queries (multi-table JOINs, CTEs, window functions) to process transactional logs and
calculate gross and net profit margins.
• Built log-log linear regression models in Python to estimate price elasticity and identify margin-draining promotional
campaigns.
• Developed interactive sales and financial Tableau dashboards for three regional branches, improving data visibility
for executive management.
• Built 14-day window event-study models to detect demand cannibalization and mitigate revenue dips.
GitHub

EDUCATION
Lutsk National Technical University Graduated: 2018
Bachelor's degree in Materials Science and Engineering. Strong foundation in mathematics, analytical modeling, and
data structuring.
Mate academy (Remote) – Data Analyst Bootcamp Graduated: 2026
Intensive, practice-driven program in SQL, Python, Google Sheets, and Tableau for business optimization.
Hillel IT School (Online) – Data Analytics Pro with AI Graduated: 2026
Data analytics with AI integration, data processing, and predictive modeling for business insights.
Hillel IT School (Online) – Business Analysis with AI In progress (expected Nov 2026)
Business analysis, requirements gathering, process modeling, and AI-powered tools for business insights and
decision-making.

LANGUAGES
Ukrainian: Native | English: B1 (Intermediate) | Polish: A2 (Pre-Intermediate)