#resume #cv #data #financial #middle #middle+ #dataanalyst #financialanalyst #bi #analyst #powerbi #sql #python #excel #googlesheets #metabase #mongodb #remote #relocation

Hi everyone,
I’m Yevhenii Chernyshev — Data / BI / Financial Analyst with 15+ years in finance and 2+ years in data analytics, including operational analytics in a logistics tech company.

I work at the intersection of finance, operations, and data, turning raw, messy datasets into clear dashboards, forecasts, and business decisions.

🔹 Core expertise

📊Data / BI Analytics
End-to-end analytics: data extraction, transformation, modeling, dashboards & automation.
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, and operational profitability.

🚕 Operational / Logistics Analytics
– Order flow, delivery performance, SLA tracking
– Courier performance, distance & route metrics
– Surcharges, system income vs courier income
– Transaction and payment analytics
– Large datasets (~10m+ orders), 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 (advanced), Google Sheets, PowerQuery, VBA, AppScript
Databases: PostgreSQL, MongoDB
Other: ETL automation, REST API, JSON/XML, Git, Jupyter

🔹 Key Achievements
– Built operational BI system for logistics data (orders, couriers, payments, routes)
– Designed data models and dashboards combining financial + operational metrics
– Automated reporting across departments (finance, ops, management)
– Created forecasting models improving planning accuracy
– Identified inefficiencies that helped reduce operational costs
– Regular ad-hoc deep dives into product, financial, and operational data

🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation

📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo