Yaroslav

Yaroslav Mailo SUMMARY
Data Analyst with hands-on experience in BigQuery SQL, Python, Tableau,
Data Analyst and statistical testing, backed by 7+ years of experience in European
logistics. Skilled in star-schema data modeling, analytical pipelines, and
business-focused dashboards. Strong focus on data quality, with practical
experience identifying missing prices, inflated A/B conversions, and distorted
route KPIs. Leverages expertise in rate analysis, tender evaluation, and fleet
operations to support data-driven decisions. English — Intermediate+.

EXPERIENCE
Data Analyst
[відкрити контакти](див. вище в блоці «контактна інформація») 04/2026 – Present | Lviv, Ukraine / Remote
[відкрити контакти](див. вище в блоці «контактна інформація») Developed 3 end-to-end analytical pipelines using BigQuery SQL, Python,
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and Tableau
Lviv, Ukraine · Remote Cleaned and validated 10k+ rows of raw data, including missing values,
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linkedin duplicates, and metric grain checks
Calculated business and experiment metrics; applied statistical tests across
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t.me/Yaroslav_Mailo 4 A/B evaluation scenarios
Designed 3 interactive dashboards for revenue, conversion, and logistics
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performance analysis
SKILLS Portfolio:
Spreadsheets — Google Sheets, Excel, Pivot E-commerce Sales Performance Analysis: investigated $32M revenue
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Tables, Data Cleaning, Visualization across 350K+ sessions by channels, devices, and segments; identified that
SQL — BigQuery, Advanced Queries, Joins, a late-January revenue drop was caused by missing price values, not a real
Window Functions, CTEs, Query Optimization sales decline
Python — Pandas, NumPy, Matplotlib, Seaborn, Link: GitHub Tableau
Exploratory Data Analysis (EDA) A/B Testing & Statistical Significance: engineered a Python pipeline for 4
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Tableau — Interactive Dashboards, Data conversion metrics across 4 A/B tests; corrected inflated significance
Storytelling, Publishing results caused by counting event rows instead of unique sessions
Statistics — Sampling, Hypothesis Testing, Link: GitHub Tableau
Correlation, Statistical Significance Logistics Data Warehouse: transformed raw logistics data into a BigQuery
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A/B Testing — Planning, Analysis, Reporting star schema and Tableau dashboard; analyzed revenue, €/km, and route
Other Tools — Jupyter Notebooks, Google efficiency, and flagged internal trips as non-comparable for commercial
Analytics, Git metrics
Languages — English (Intermediate+), Polish Link: GitHub Tableau
(Intermediate+), Ukrainian (Native)
PREVIOUS EXPERIENCE
EDUCATION Supply Chain & Transport Operations Specialist
Lviv Institute of Economics and Tourism EU, UK & CH Markets
Master’s Degree in Entrepreneurship, Trade and 07/2023 – 04/2026
Exchange Activities Managed operational and financial data across 15+ European transport
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2014 – 2019 corridors
Monitored cost, delivery, capacity, and service KPIs across 13+ fleet trucks
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to evaluate performance
ADDITIONAL EDUCATION Evaluated tenders, market rates, and pricing strategies to identify
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Data Analyst course profitable opportunities
Mate academy Prepared market analysis and cost-benefit reports, presenting pricing
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recommendations to company owners and management
04/2026 – Present
Leveraged Excel, Google Sheets, and Abona TMS for KPI tracking, pricing
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SQL (Advanced) Certificate analysis, and operational data management
HackerRank Senior Freight Broker
06/2026 Hegelmann Group
Link: Google Drive 12/2018 – 08/2023 | Lviv, Ukraine
Sourced and priced freight using daily market and rate data from
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TIMOCOM, LKW Walter, and Trans.eu
Assessed market rates, route profitability, and shipment margins to
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support buy/sell decisions
Tracked profit performance across 50+ carriers and maintained shipment
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data using Excel and Abona TMS
Created a carrier database and mentored new brokers in pricing analysis
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and market evaluation