Особисті дані приховані Ветеран

VADYM KAPILEVYCH
Junior Data Analyst
[відкрити контакти](див. вище в блоці «контактна інформація») (WhatsApp) [відкрити контакти](див. вище в блоці «контактна інформація») Kyiv, Ukraine
[відкрити контакти](див. вище в блоці «контактна інформація»)

SUMMARY
Junior Data Analyst with 4+ years of research experience in the MilTech domain, skilled in SQL,
Python (Pandas, NumPy, Matplotlib, Seaborn), Tableau, Power BI. Completed analysis within
10+ scientific publications in the field of data-centric IT solutions, provided valued outcomes with
the implications for improving data-driven decision-making. Leverage my analytical and
technical skills to solve the issues challenging the product development and its evolution.
Seeking the position in friendly team with an innovative environment to apply my skills and
multiply experience.
HARD SKILLS: RDBMS, SQL, python, DAX, EDA, A/B testing, product analysis (ARPU, LTV,
CAC, Retention, Churn, Conversion, DAU/WAU/MAU), mathematical statistics, advanced
analytics, data cleaning, data visualization.
TOOLS: Tableau, Google Data Studio, Google Sheets, Google Colab, Jupyter Notebook,
BigQuery, Microsoft Excel, PowerBI, Power Query, Google Analytics, Amplitude, DBeaver,
PostgreSQL, MySQL, LiteSQL, Pandas, Numpy, Seaborn, Matplotlib.
SOFT SKILLS: Disciplined, focused, accurate, eager to learn.
PROJECT EXPERIENCE
User Retention and Cohort Analysis by Acquisition Channel
https://docs.google.com/spreadsheets/d/1s008hALYkQtcPEzRt5PBUesWtx3prOP-CzJUXz6NkzY/edit?usp=sharing
Tools: SQL (PostgreSQL), DBeaver, Google Sheets, Cohort Analysis, Data Visualization.
Description: Developed an end-to-end cohort analysis solution to evaluate user retention and
acquisition quality across promotional and organic channels. Processed raw data of user
registration and their activities, engineered cohort-based retention model, and built interactive
dashboards to identify retention patterns and user engagement trends during the first months of
the customer lifecycle.
My Tasks:
● extracted and transformed user activity data using SQL, cleaned and standardized date
fields from multiple text formats using SQL date parsing and transformation;
● merged user registration and event datasets to establish a unified analytical data model;
● calculated user cohorts, activity months, and customer tenure (month offsets);
● designed aggregated cohort datasets for retention analysis and reporting;
● built interactive cohort tables and retention matrices in Google Sheets using pivot tables,
conditional aggregation, and dynamic filtering; implemented conditional formatting and
heatmap visualizations to highlight retention trends;
● created interactive slicers to analyze retention by acquisition source (promotional vs
organic); conducted analysis of user behavior across acquisition channels;
● evaluated acquisition quality and retention performance throughout the customer lifecycle;
calculated KPIs (key metrics) such as Retention Rate, Cohort Size, Active Users, Monthly
Retention, User Tenure (Month Offset), Acquisition Quality, Promotional vs Organic User
Retention.
Result:
● delivered recommendations for marketing campaigns optimization to emphasize the
product's long-term value proposition rather than focusing primarily on discounts and
promotional offers;
● identified the need for implementing a staged incentive strategy, where bonuses, rewards,
and discounts are distributed progressively throughout the customer lifecycle to encourage
sustained engagement and improve retention;
● suggested enhancing onboarding and user education processes to help newly acquired
users better understand the product's benefits and increase long-term adoption.
Analytics and Time Intelligence in Academic Performance Overview
https://drive.google.com/drive/folders/1h9w8yruXCO1GCjJaFizPjYFZu00Mcrh1?usp=sharing
Tools: PowerBI, SQL, Google Sheets, A/B testing, Cohort Analysis.
Description: Reviewed the academic progress among the students, performed the analysis of
attendance and their progress. Delivered a dashboard with ad-hoc metrics, KPIs and graphs
that displayed the analysis results in realm of time, categories and acceptable limits.
My tasks:
● designed data model and relationships between educational datasets, collected and
transformed educational data;
● created DAX measures and defined KPIs for academic performance analysis;
● completed exploratory data analysis to identify performance patterns and anomalies;
● implemented interactive visualizations and optimized dashboard usability by drill-down and
filtering capabilities;
● analyzed relationships between attendance, engagement, and academic outcomes.
Result:
● improved visibility into student achievement data, enabled clear understanding of abnormal
values in academic performance;
● provided data-driven support to optimize for upcoming academic year.
WORK EXPERIENCE
Center for Military and Strategic Studies
Leading Researcher
https://orcid.org/0000-0001-9025-7608
Nov 2021 - Jun 2026
● performed comprehensive data analysis and comparative assessments of international data
management standards;
● investigated data marking in the cloud-based environment to improve data management.
Revised the data-related issues of IT military projects to facilitate their implementation;
● refined the role of active metadata in data management, enhancing interoperability and
decision-support capabilities through targeted research reports, analytical papers, and
recommendations for leadership and decision-makers.
Achievements:
● analyzed 51 standards (4172 pages), identified 2 key areas for strategic improvement,
initiated specific part of a taxonomy-like descriptive catalog of technical services;
● collaborated 3 researches, 2 scientific tasks and produced 10+ articles, thesis and reports in
the areas of metadata management, data-centric security, data integration in cloud-based
environment, usage of active metadata, metadata label services, generated 5+ detailed
reports impacting decision-making processes, defined data requirements for 2 projects.
Armed Forces of Ukraine
Military positions, mostly by technical specialty
Jul 2004 - Nov 2021
● managed multidisciplinary teams, oversaw organizational planning, coordinated and
streamlined consulting processes for IT initiatives, supporting project implementation;
● collaborated with contractors and international partners to facilitate knowledge sharing.
Achievements:
● coordinated 1st and 2nd Ukrainian Defense Hackathons focused on solving IT challenges.
EDUCATION
GoIT – Data Analyst (2026); Kaggle – Python (2026); DataCamp – Intermediate Python (2026);
The U.S. Army War College – “From Data to Better Decisions” (2021);
ITEA – Agile PM Course (2019); ITEA – PM course (2018);
National Technical University of Ukraine „Kyiv Polytechnic Institute‟: Bachelor‟s degree,
Computer Science (1999-2003), Specialist‟s degree, Computer Science (2003-2004).
LANGUAGES:
English – Upper-Intermediate; Ukrainian – Native