#resume #cv #data #dataanalyst #financialanalyst #bi #powerbi #sql #python #excel #googlesheets #fintech #payments #reconciliation #automation #ai #remote #relocation

Hi everyone,
I’m Yevhenii Chernyshev, Data / BI / Financial Analyst with 15+ years in finance and 2+ years in data analytics.
My main focus is financial analytics, fintech/payments, reconciliation, BI reporting, and automation of messy operational and financial data.
I work at the intersection of finance, operations, and data: turning raw datasets into dashboards, automated pipelines, reconciliation logic, forecasts, controls, and business decisions.

🔹Core expertise:
📊Data / BI Analytics
- Data extraction, transformation, modeling, dashboards, reporting automation, and data quality checks
- Power BI, Tableau, Metabase, Looker Studio
- Management dashboards for financial, operational, and transaction data

💼Financial & Unit Economics Analytics
- P&L, Cash Flow, Budget vs Actual, forecasting, margin analysis
- Unit economics, revenue streams, cost structure, transaction flows, payment logic, and operational profitability

🏦Fintech / Payments / Reconciliation
- Python / MSSQL pipelines for PSP reconciliation and transaction matching
- Rebuilt cascaded provider transaction logic and restored parent-child transaction matching
- Improved reconciliation coverage from around 70-80% to near-complete matching
- Automated exception reports, summary reports, issue reports, and validation checks
- Worked with PSP amount logic, fees, chargebacks, refunds, unmatched transactions, and amount mismatches
- Built Rolling Reserve logic: MID mapping, tariff mapping, FX conversion, RR accruals, caps, release schedules, and BI-ready outputs

🚕Operational / Logistics Analytics
- Order flow, delivery performance, SLA tracking
- Courier performance, route and distance metrics
- Surcharges, system income vs courier income
- Large datasets and multi-table data models
- DWH logic from raw operational data

🏦Product / Business Analytics
- Funnels, cohorts, retention, LTV, segmentation, KPI systems, and A/B logic support

AI-assisted analytics & automation
- Recently completed Claude Code 101 by Anthropic
- Also completed: Claude Code 101
- I use AI tools for analytics workflow acceleration, Python/SQL support, data cleaning, documentation, validation, and automation
- Focused on responsible AI use: result validation, data privacy, and clear human accountability

🔹Tech Stack:
- Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
- SQL: PostgreSQL, MSSQL, BigQuery, MySQL, complex joins, CTEs, window functions
- BI: Power BI, Tableau, Metabase, Looker Studio
- Data tools: Excel, Google Sheets, PowerQuery, VBA, Apps Script
- Databases: PostgreSQL, MongoDB
- Other: ETL automation, REST API, JSON/XML, Git, Jupyter, Google Drive/Sheets API, Claude Code

🔹Key achievements:
- Built BI systems for logistics, financial, and transaction data
- Designed dashboards combining financial, operational, and payment metrics
- Improved reconciliation coverage from around 70-80% to near-complete results
- Rebuilt cascaded transaction logic and restored provider transaction matching
- Automated reconciliation, exception reporting, Rolling Reserve calculations, and data quality controls
- Identified legacy data and transaction issues affecting financial reporting and reconciliation accuracy
- Regular ad-hoc deep dives into product, financial, operational, and transaction data

🔹Languages & format:
English - B1+/B2 working level
German - A2
Russian - native
Ukrainian - native

Remote / full-time / B2B
Open to relocation

CV: Notion CV + portfolio
TG: @Yevhenii_successo