Максим

MAKSYM MYNKO
Junior Data Analyst
[відкрити контакти](див. вище в блоці «контактна інформація») [відкрити контакти](див. вище в блоці «контактна інформація») Merefa, Ukraine
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SUMMARY
Junior Data Analyst with 3+ years experience in Sales and Digital Marketing. Analyzing user
behavior and conversion metrics inspired me to pursue a career as a data analyst. I have
skills in exploratory data analysis, SQL, Python (Pandas, NumPy), Power BI, Tableau, data
visualization, and A/B testing. I am focused on my own professional development and on
increasing my team’s overall revenue.

HARD SKILLS: SQL, Python, Advertising companies analysis, Gathering of the Requirements
Theory of Probability and Mathematical Statistic, A/B Tests, Product Analysis, Business
metrics, Data Visualization, Data Storytelling, Data Cleaning & Validation.
TOOLS: Tableau, Power BI, Looker Studio, Amplitude, Google Analytics, DBeaver, BigQuery,
Google Sheets, Excel, Pandas, NumPy, Matplotlib, Seaborn, Jupyter Notebook.
SOFT SKILLS: Customer focus, Attention to detail, Responsibility, Curiosity, Logical thinking.

PROJECT EXPERIENCE
E-commerce Conversion Funnel
Tools: SQL (BigQuery), Tableau
Description: Create a dashboard for analyzing the conversion funnel in the online store for
managers in the marketing department.
My tasks: Prepared and processed data using SQL. Created charts, metrics,
LOD calculations, and filters in Tableau.
Result: The conversion funnel can be analyzed using various marketing metrics.
I recommend investigating why users are skipping the “Add to Cart” step in the funnel. Is
this due to technical issues, or does the website have a “Buy Now” button?

HR Compensation Analysis
Tools: Google Sheets, SQL (BigQuery), Google Data Studio
Description: Analyze the salaries of active employees. Calculate the total payroll and
compare average employee salaries by city, position, and experience.
My tasks: Data preparation and cleaning. SQL analysis. Dashboard creation. Draw
conclusions and provide recommendations.
Result: I conducted an analysis and built a dashboard. The conclusions and
recommendations are posted on the “Summary” sheet in Google Sheets.
Links to the SQL and the dashboard are available in Google Sheets.

Cross-channel marketing mix analytics
Tools: SQL, Tableau
Description: Develop an interactive marketing dashboard in Tableau Public based on data
from advertising campaigns from two different sources.
My tasks: Data cleaning and preparation. Calculation of the necessary metrics. Configuring
parameter, filters, and action to improve the dashboard's usability.
Result: The dashboard provides information on key metrics for each ad source and
campaign. Increasing the advertising budget directly leads to an increase in the number of
leads.

Assessing user retention rate based on cohort analysis
Tools: PostgreSQL (DBeaver), Google Sheets
Description: Create a table to compare the behavior of two user groups. Draw conclusions
about the quality of customer acquisition and retention.
My tasks: Data processing and visualization. User behavior analysis. Providing retention
improvement recommendations.
Result: The differences between user groups have been identified. Recommendations have
been provided for more effective customer engagement.

EDUCATION
GoIT - start your career in IT National Technical University «Kharkiv Polytechnic
Data Analyst
Institute»
Computer Systems and Networks
2026
2006-2012

LANGUAGES
English - Pre-Intermediate
Ukrainian - Native