Герман
Дата-аналітик
- Considering positions:
- Дата-аналітик, Аналітик баз даних, Системний аналітик, Аналітик консолідованої інформації, Web-аналітик, Finance analyst, Аналітик з маркетингу, Бізнес-аналітик, IT-спеціаліст, Розробник BI
- Age:
- 29 years
- City of residence:
- Okhtyrka
- Ready to work:
- Remote
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DATA ANALYST
da.german.rusanov@gmail.com [
SUMMARY
Data Analyst with skills in SQL, Python (Pandas, NumPy), Tableau, and Google Sheets. Experienced in data
cleaning, analysis, and visualization to support business decisions. Background in sales, marketing, and CPA
advertising with hands-on experience analyzing campaign performance, customer behavior, and revenue
metrics. Skilled in working with e-commerce and sales data, building dashboards, and delivering clear
insights. Able to work independently in challenging conditions.
EXPERIENCE
Marketing Analyst, HayCredito 02/2026 – 04/2026
Analyzed contact center funnel (registration → revision → accept)
• Remote
Worked with SQL (CTE, window functions, JOIN, LATERAL)
•
Evaluated operator performance (45+ sec calls, conversion, issuance)
•
Built reports and analyzed conversion and bottlenecks
•
Data Analyst, Self-Employed 11/2025
Analyzed sales and e-commerce data to identify trends and customer behavior
•
Built dashboards using Google Sheets, SQL (BigQuery), Python, and Tableau
•
Cleaned and transformed multi-source datasets for reporting and insights
•
CPA Media Buyer, Everad 01/2021 – 02/2022
Managed Facebook Ads and Google Ads campaigns
•
Analyzed CPA, ROI, and conversion performance
•
Created ad creatives and landing content
•
Call-Center Team Leader, Everad 06/2020 – 01/2021
Supervised a sales team and monitored KPIs
•
Analyzed results and conducted performance reviews
•
Sales Manager, Everad 11/2017 – 06/2020
Managed inbound/outbound customer communications and identified client
•
needs
Presented products and handled the full sales cycle
•
Worked with sales metrics and performance tracking
•
EDUCATION
Bachelor's Degree in Cybersecurity (incomplete), 2014 – 2018
Kharkiv National University of Radio Electronics Kharkiv, Ukraine
SKILLS
Spreadsheets SQL
Pivot Tables
• Advanced Queries
•
Data Cleaning
• Window Functions
•
Visualization
• Query Optimization
•
Common Table Expressions (CTE)
•
Python
Pandas
• Tableau
NumPy
• Interactive Dashboards
•
Matplotlib
• Data Storytelling
•
Seaborn
• Publishing
•
Exploratory Data Analysis (EDA)
•
A/B Testing
Statistics Planning
•
Sampling
• Analysis
•
Hypothesis Testing
• Reporting
•
Correlation
•
Statistical Significance
•
Other Tools
Jupyter Notebooks
•
Google Analytics
•
Excel
•
Git
•
Languages
English
Upper-Intermediate
ADDITIONAL EDUCATION
Intermediate SQL
Statistics SQL
Advanced Data Analyst Full-Time Course
ACHIEVEMENTS
Winner of City Football Cup 01/12/2012
Winner of City Physics Olympiad 01/12/2008
Portfolio
Project 1 (Spreadsheets) ,
Sales dynamics analysis by category, product, and country Tools: Google Sheets, Pivot Tables
Visualized sales trends and built a dynamic dashboard
•
Applied ABC analysis to identify high-impact products
•
Project 2 (SQL) , E-commerce Analysis & Visualization Tools: BigQuery, SQL, Looker
Analyzed user behavior and segmented customers by traffic source
•
Queried and cleaned multi-table datasets to extract insights on conversions
•
Project 3 (Python) ,
E-commerce Data Analysis Dashboard Tools: Python, Pandas, NumPy, Matplotlib, Seaborn, Tableau
Created a structured analysis report with visualizations and business insights
•
Analyzed revenue and key metrics across categories, devices, and countries
•
Project 4 (SQL, Python, Tableau) , E-commerce Sales Performance & Statistical Analysis Tools: Python,
Pandas, NumPy, Matplotlib, Seaborn, SciPy, Google Colab, Tableau
Analyzed 91 days of session-level e-commerce data
•
Identified key revenue drivers, regional trends, and top product categories
•
Applied statistical testing and evaluated marketing channel performance
•
Project 5 (A/B Testing, Python, SQL, Tableau) ,
A/B Test Statistical Significance Analysis Tools: BigQuery, SQL, Python, Pandas, SciPy, Google Colab, Tableau
Aggregated session-level data and calculated KPI conversion rates
•
Validated experiment (SRM) and ran two-sample Z-tests at total and segment levels
•
Identified statistically significant funnel changes across devices, channels, and countries
•
Prepared a Tableau-ready dataset and built a dashboard for control vs test comparison
•
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