Channels / User Profile
User Info
Yevhenii
| ID | 5843798463 |
|---|---|
| Type | user |
| Username | @Yevhenii_Successo |
| First Name | Yevhenii |
| First Seen | 2026-01-11 09:15 UTC |
| Updated | 2026-01-11 09:15 UTC |
Statistics
Total Messages: 15
Active in: 1 channel(s)
Activity by Channel
Recent Messages
📄 Document (not supported)
#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
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
📄 Document (not supported)
#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
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
📎 Webpage (not supported)
#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 analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
Hi everyone
I’m Yevhenii Chernyshev — Data / BI / Financial Analyst with 15+ years in finance and 2 years in analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
📄 Document (not supported)
#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 analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
Hi everyone
I’m Yevhenii Chernyshev — Data / BI / Financial Analyst with 15+ years in finance and 2 years in analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
📄 Document (not supported)
#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 analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
Hi everyone
I’m Yevhenii Chernyshev — Data / BI / Financial Analyst with 15+ years in finance and 2 years in analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
📄 Document (not supported)
#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 analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
Hi everyone
I’m Yevhenii Chernyshev — Data / BI / Financial Analyst with 15+ years in finance and 2 years in analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
📄 Document (not supported)
#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 analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
Hi everyone
I’m Yevhenii Chernyshev — Data / BI / Financial Analyst with 15+ years in finance and 2 years in analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
📄 Document (not supported)
#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 analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
Hi everyone
I’m Yevhenii Chernyshev — Data / BI / Financial Analyst with 15+ years in finance and 2 years in analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
📄 Document (not supported)
#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 analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
Hi everyone
I’m Yevhenii Chernyshev — Data / BI / Financial Analyst with 15+ years in finance and 2 years in analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
📄 Document (not supported)
#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 analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo
Hi everyone
I’m Yevhenii Chernyshev — Data / BI / Financial Analyst with 15+ years in finance and 2 years in analytics.
I connect finance, business, and data to help teams make better decisions.
🔹 Core areas I cover
Business / Product Analytics – metrics (DAU/MAU, LTV, Retention), A/B tests, funnels, cohort & segment analysis
Financial Analytics – P&L, Cash Flow, Budget vs Actual, Unit Economics, forecasting (Python / Power BI / Excel)
Data / BI Analytics – ETL pipelines, dashboards (Power BI, Metabase, Tableau, Looker Studio), automation, SQL optimization
Marketing / Sales Analytics – channel performance, ROMI/ROI, RFM, segmentation & sales forecasting
🔹 Stack & Tools
Python: pandas, numpy, matplotlib, seaborn, scikit-learn, Prophet, statsmodels
SQL: PostgreSQL, MSSQL, BigQuery, MySQL, SQLite — complex joins, window functions, CTEs, ad-hoc analytical queries
BI: Power BI, Tableau, Metabase, Google Looker Studio
Data: Excel, Google Sheets, PowerQuery, VBA, AppScript
Databases: MongoDB, PostgreSQL
Other: Git, Jupyter, REST API, JSON/XML, ETL automation tools
🔹 Achievements
– Automated financial and operational reporting across departments
– Built interactive Power BI & Metabase dashboards for management
– Designed SQL & MongoDB models for transaction analytics
– Created Python forecasting models improving accuracy by 20%
– Delivered insights that helped reduce operational costs by 15%
– Solved ad-hoc analytical tasks for finance, product, and operations teams (SQL + Power BI)
🔹 Languages & format
English — B1 | German — A2 | Russian — native | Ukrainian — native
Remote / full-time / B2B | Open to relocation
📎 CV: Notion CV + portfolio**
📱 TG: **@Yevhenii_successo