#resume #cv #data #financial #middle #middleplus #dataanalyst #financialanalyst #bi #analyst #powerbi #sql #python #excel #googlesheets #metabase #mongodb #fintech #payments #reconciliation #remote #relocation
Hi everyone,
I’m Yevhenii Chernyshev, Data / BI / Financial Analyst with 15+ years in finance and 2+ years in data analytics, including fintech, payments, reconciliation, BI, and financial data automation.
I work at the intersection of finance, operations, and data, turning raw and messy datasets into clear dashboards, automated pipelines, reconciliation logic, forecasts, and business decisions.
🔹 Core expertise
📊 Data / BI Analytics
End-to-end analytics: data extraction, transformation, modeling, dashboards, reporting automation, and data quality checks.
Built operational and financial dashboards used by management for daily decision-making.
💼 Financial & Unit Economics Analytics
P&L, Cash Flow, Budget vs Actual, forecasting, margin analysis, cost structure optimization.
Strong focus on unit economics, revenue streams, transaction flows, payment logic, and operational profitability.
🏦 Fintech / Payments / Reconciliation
Built Python / MSSQL pipelines for PSP reconciliation, transaction matching, and financial control
Rebuilt Special transaction chain logic for cascaded provider flows
Restored correct parent-child transaction matching across multiple providers
Improved reconciliation coverage from around 70-80% to near-complete matching
Automated issue reports, summary reports, exception reports, and validation checks
Investigated legacy transaction issues from 2024-2025 that had not been detected before
Worked with PSP amount logic, fee calculation, 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, distance and route metrics
Surcharges, system income vs courier income
Transaction and payment analytics
Large datasets, multi-table data models
Building DWH logic from raw operational data
🔹 Product / Business Analytics
Funnels, cohorts, retention, LTV, segmentation, KPI systems, A/B logic support.
🔹 Tech Stack
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, complex joins, window functions, CTEs
BI: Power BI, Tableau, Metabase, Looker Studio
Data tools: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: PostgreSQL, MongoDB
Other: ETL automation, REST API, JSON/XML, Git, Jupyter, Google Drive/Sheets API
🔹 Key Achievements
Built BI systems for logistics, financial, and transaction data
Designed data models and dashboards combining financial, operational, and payment metrics
Improved reconciliation coverage from around 70-80% to near-complete results
Rebuilt cascaded transaction logic and restored correct 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 - B2 | German - A2 | Russian - native | Ukrainian - native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo