CRM/Retention-менеджер · finance

#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**](https://verify.skilljar.com/c/kgxcfga85an4) - 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