Anhelina

Anhelina Bohdanova
Data / Product Analyst

Contact
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Khmelnytskyi, Ukraine | Remote

Summary
Analyst with 4+ years in digital projects – two in software development, two in project management, with analytics embedded
in both. I work with SQL, Python, BigQuery and Tableau, and apply statistical methods, A/B testing and EDA.

Worked with delivery and financial metrics – velocity with bootstrap confidence intervals, DORA, cost and margin scenarios –
used for team, budget and process decisions. Automated data collection with n8n and AI tooling. Run independent analytics
projects: A/B testing, EDA, campaign metrics, dashboards in Tableau/Looker. Excited to bring this into a product or data
analyst role.

Skills
SQL (Window Functions, CTEs, Query Optimization)
BigQuery, Firebase (Querying, Data Extraction)

Python (pandas, NumPy, Matplotlib, Seaborn)
Product Metrics (Conversion, Acquisition Channels,
A/B Testing (Design, Analysis, Reporting)
Revenue & Profitability, Seasonality)

Statistics (Hypothesis Testing, Confidence Intervals, Delivery Metrics (DORA, Velocity, Escape Rate)

Bootstrap, Sampling)
Postman, REST APIs (Data Extraction, Endpoint
Exploratory Data Analysis (Profiling, Cleaning, Testing)

Segmentation)
Workflow Automation (n8n, Automated Reporting)

Google Sheets, Excel (Pivot Tables, Cleaning, AI Tooling (Claude, Cursor – Analysis, Automation)

Visualization)
Jupyter Notebooks, Git

Tableau, Looker (Interactive Dashboards, Data Storytelling) GA4 Event Data (Sessions, Events, Channel Attribution)

work Experience
Data Analyst, Jan 2025 – Present
Designed and analy zed A/B tests end to end in Python – hypothesis, primary and secondary metrics, traffic allocation,
group distribution checks, significance testing – with documented conclusions and rollout recommendations.

Ran EDA in Python (pandas, NumPy) across e-commerce, sales and marketing datasets – user behavior, acquisition
channels, profiling, data quality checks, segmentation, accounting for multiple-comparison risk, surfacing anomalies and
attribution issues, and documenting findings with recommendations.

Built dashboards in Tableau for A/B test monitoring – sample ratio checks, statistical significance, segment breakdowns –
and for sales and email campaign performance.

Wrote analytical SQL over BigQuery for reporting and metric consolidation – window functions, CTEs, aggregations and
views across multiple levels of granularity.

Analyzed paid campaign performance in Google Sheets against business targets and produced per-campaign
recommendations and action plans.
Project Manager at Speed and Function, Jun 2024 – Present
C oordinated and ran an enterprise project to handover – 2-5 engineers, budget, delivery and client stakeholders, with
additional projects in parallel.

Analyzed team velocity with bootstrap confidence intervals in Python to improve sprint estimation, reducing carry-over
from 5 tickets per sprint to under 2.

Tracked and acted on delivery metrics with the team (DORA, uptime, cost, escape rate): cut unnecessary spend,
prioritized test automation, and held system stability while preserving project margin.

Modeled team-composition scenarios (headcount, rates, margin) used to negotiate team structure with the client.

Cut documentation time 60% by automating generation with n8n and AI tools; automated resource-allocation data
collection.

Restructured and cleaned 3 years of client Jira and Confluence data using AI tools.

Full-stack Developer at Senseteq, Aug 2022 – May 2024
Built logic for collecting product usage data to track business metrics.

Developed features with the team across 4 client projects with React, JavaScript, Firebase: CRUD operations, data
collection, databases, backend services.

Led client communication and wrote the documentation the team used to plan each iteration.
Trainee Full-stack Developer at Fractal Academy, Jul 2021 – Jun 2022
Full-stack training program – CS, algorithms, data structures; built 3+ team projects with Firebase, React and JavaScript,
one presented to a European client.

portfolio
A/B Test Significance Analysis
Evaluated four A/B tests on an e-commerce store across four conversion metrics each, checking group distribution and
statistical significance. Broke results down by segment and accounted for the inflated false-positive risk of running many
comparisons at once.
E-commerce EDA
Explored an e-commerce dataset to understand where revenue comes from – acquisition channels, user behavior,
seasonality – and how stable those patterns are. Used bootstrap confidence intervals to separate real differences between
segments from random variation.
Store Effectiveness Analysis
Analyzed store performance across revenue, profitability, product popularity and operational efficiency, including how each
shifts by season.
SQL – Email Campaign Performance
Consolidated email campaign metrics at account and email level, ranked markets by performance and filtered to the top 10
countries. Built with CTEs and window functions.
Tableau Dashboards
A collection of dashboards on different datasets – sales, e-commerce and email campaign performance, A/B test monitoring
with sample ratio checks and significance, and exploratory dashboards on public data.

Education
Bachelor of Computer Science at Khmelnytskyi National University
Sep 2020 – Jun 2024

additional Education
Mate Academy – Data Analytics, 2025 – 2026

IAMPM – AI Booster, 2025

IAMPM – Business Analysis, 2025

Stagen – Leadership, 2024

Languages
English – C1
Ukrainian – Native