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Kapil Dev
@kapildevbhai
Senior Data and Finance Analyst: Power BI, SQL, Excel, Python, Claude
India
Inglés, Hindi, Malayalam
Sobre mí
I've spent 10+ years in data and finance at Paytm, Udaan and [24]7.ai. At Paytm I owned revenue and P&L forecasting for 3 verticals and 17 categories. I cut the daily P&L report from 18 man-hours to 30 minutes with SQL, and traced a ₹9 crore (about $1M) discrepancy by reconciling bank files in Python.
Here I build Power BI and Looker Studio dashboards, write SQL, make Excel financial models, reconcile bank data against ledgers, automate Sheets and Excel, build websites and set up Claude Code workspaces.
I've self-published 7 books, including Think in SQL and The Claude Workspace Handbook.
Habilidades
Kapil Dev
desconectado •
Revisa mis servicios
Implementación y despliegue de IA
I will set up your claude code workspace with skills, agents, hooks and mcp servers
Panel de datos
I will build power bi or looker studio dashboards from your excel or sql data
Porfolio
Experiencia laboral
Deputy Manager | Senior Data & Finance Analyst
Paytm • Tiempo completo
Jul 2021 - Sep 2026 • 5 yrs 2 mos
Owned revenue and P&L forecasting, financial validation and BI reporting for 3 business verticals and 17 categories: mobile services, utility payments, financial services, travel, ticketing and entertainment. - Validated the P&L, balance sheet, GL entries, and cost and revenue numbers for all 17 categories, so ledgers and reports stayed accurate and compliant. - Ran monthly cost provisioning and accrual schedules. Checked actual vendor and operating costs against provisions and General Ledger entries so margins didn't slip. - Forecast revenue and bottom line, tracked budgets, and worked with leadership, finance, product and operations on long-term financial plans and operating reviews. - Wrote Python (Pandas) pipelines that reconcile 20-30 bank CSV files (10L+ rows each) against our transaction systems. They recovered partner-bank discounts. The same work, with GL validation, traced a Rs 9 Cr discrepancy to its root cause and resolved it. - Built a GMV forecasting model (hourly mean + 2 standard deviations) that covered 95% of transaction patterns with 120% buffer accuracy. It stopped Rs 10-30 Cr/month in transaction failures. - Built demand-planning models that cut working-capital interest by Rs 55 Lakhs/month. - Turned a loss-making business into a Rs 3 Cr/month profit centre by cutting costs and improving revenue. - Automated the daily P&L report and dashboards with SQL, R and Excel macros. Manual effort went from 18 man-hours to 30 minutes, and P&L reporting moved from weekly to daily. - Built Looker and Google Data Studio dashboards for financial metrics, transaction performance and business trends. Tools: SQL (BigQuery, PostgreSQL), Python (Pandas), Power BI, Looker Studio, Advanced Excel, R.
