Серафим

Serafym Mitrik
Junior Data / BI Analyst

Location: Chernivtsi, Ukraine (Open to remote, hybrid, and relocation)

Phone: [open contact info](look above in the "contact info" section)

Email: [open contact info](look above in the "contact info" section)

LinkedIn: [open contact info](look above in the "contact info" section)

GitHub: github.com/pipserrr

PROFESSIONAL SUMMARY

Detail-oriented Data & BI Analyst with a strong focus on E-commerce and Sales analytics.
Skilled in building end-to-end analytical pipelines—from data extraction and cleaning in
Python to Star Schema modeling and interactive visualization in Power BI. Proven ability to
transform raw data into actionable business insights, such as identifying revenue leakage,
analyzing customer churn via RFM segmentation, and evaluating product sentiment.

TECHNICAL SKILLS

● BI & Visualization: Power BI, DAX, Power Query, Data Modeling (Star Schema),
Dashboard Design.
● Data Processing & Programming: Python (Pandas, Requests, JSON), API
Integration, Text Mining / NLP heuristics.
● Databases: SQL (PostgreSQL/MySQL, JOINs, CTEs, Window Functions,
Aggregations).
● Tools: MS Excel (Advanced Formulas, Pivot Tables), Git, GitHub.
● Business Analytics: Sales & Financial KPI Tracking, RFM Analysis, Sentiment
Analysis, Margin Analysis, YoY Trends.

PORTFOLIO PROJECTS

E-Commerce Analytics & AI Customer Feedback Dashboard | Python, REST API, Power
BI, DAX Link to GitHub

● Engineered an end-to-end ETL pipeline in Python using requests to extract paged
e-commerce data (Orders, Customers, Products, Reviews) via REST API,
successfully flattening nested JSONs into relational tables.
● Developed a rule-based Text Mining script in Pandas to automatically categorize
negative customer reviews (e.g., Logistics, Quality, Pricing), saving business costs on
external LLM APIs.

● Designed a Power BI dashboard with a Star Schema data model and custom DAX
measures, identifying that 62% of negative feedback stemmed from "Customer
Service" rather than pricing or delivery.
● Performed RFM segmentation, highlighting a 37% "At Risk" and "Lost" customer
base, providing actionable data for targeted marketing retention campaigns.
● Identified low-rating products generating high revenue, enabling management to
address quality issues affecting Customer Lifetime Value (LTV).

Sales & Financial Analytics Dashboard | Power BI, DAX, Python, MS Excel Link to GitHub

● Built a comprehensive 4-page Power BI dashboard analyzing operational and
financial metrics across historical sales data (2020–2023).
● Automated multi-currency price conversion by writing a Python (Pandas) script to
parse and merge historical exchange rate data, ensuring accurate financial reporting.
● Created a robust data model with a custom Date Table and implemented DAX
measures to calculate YoY growth, gross/net margins, and median sales.
● Identified the top-performing product categories driving the majority of total revenue
and isolated low-margin regions to help optimize logistics and pricing strategies.

COURSES & CERTIFICATIONS

● Microsoft — Power BI Data Analyst Professional Certificate (Coursera) | 2026
● IBM — Data Analysis with Python (Coursera) | 2026
● Google — Introduction to Git and GitHub (Coursera) | 2026
● University of Michigan — Python for Everybody (Coursera) | 2026

LANGUAGES

● English: Intermediate (B1)
● Ukrainian: Native