Denys

Denys Brativnyk
Technical/Operations Analyst

Detail-oriented Computer Engineering student with a foundation in
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Python, SQL, and data analysis. Experienced in working with
structured datasets, building dashboards, and translating data into
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actionable insights. Comfortable operating at the intersection of
technical and business tasks, with hands-on experience across
📍 Lviv, Ukraine PostgreSQL, Tableau, and Excel. Quick learner with a structured
approach to problem-solving and delivering reliable results.
EXPERTISE
Languages: Python, Swift, C, C++
 experience

Data & Analytics: SQL, Excel, Google
Sheets
 Junior iOS Developer at Etnocode

Databases: PostgreSQL
 June 2025 – November 2025

Visualization: Tableau, Google Sheets
Developed and maintained features for a commercial iOS app

Charts
 Collaborated with development team in Agile environment

Tools: DBeaver, Jupyter Notebook, Worked with REST API integration and data management

REST API, JSON, Postman, G it, G itHub,
G itLab

Pet projects
Testing: Unit Testing

Collaboration: Agile/Scrum
Payment Transactions Analysis

Analyzed 6.3M simulated mobile transactions to identify fraud
Education patterns across 5 transaction types

Found fraud limited to TRANSFER and CASH_OUT; platform
Bachelors Degree in Computer detection rate was only 0.19%

Engineering

2021 — 2025

Identified behavioral red flags: top senders made single transfers
of tens of millions

Masters Degree in Computer Science Link: GitHub | Tableau Public

(in progress) Department of Artificial Stack: PostgreSQL, DBeaver, Tableau Public

Intelligence Systems | Data Analytics
track
Physiological Stress Detection EDA

2025 — 2026

Performed EDA on multi-subject WESAD dataset using BVP and
Lviv Polytechnic National University
EDA physiological signals

Visualized stress vs baseline patterns with annotated time series
L anguages and cross-subject comparisons

Connected to graduate research on federated learning for stress
🇺🇦 Ukrainian – Native speaker
detection

🇬🇧 English – B2 Link: GitHub

Stack: Python, Jupyter Notebook, SciPy

Brazilian E-Commerce Analysis

Analyzed 9-table Olist relational dataset covering orders, sellers,
payments, and reviews

Identified top revenue categories, delivery performance by state,
and seller rankings

Built multi-sheet Tableau dashboard with geographic map and
dynamic filters

Link: GitHub | Tableau Public

Stack: PostgreSQL, DBeaver, Tableau Public

Superstore Sales Analysis

Structured raw data into 4 analytical sheets with VLOOKUP,
UNIQUE, and SUMIF formulas

Built interactive dashboard with pivot charts, KPI cards, and
slicers for Region and Category

Link: Google Sheets

Stack: Google Sheets, Excel