Supply chain operations analyst who'd rather let a clean SQL query do the arguing. Currently making warehouses across India a little less chaotic, one query at a time.
Mechanical engineer by training, data nerd by choice. Somewhere along the way I figured out spreadsheets and SQL queries were way more fun than gear ratios — and here we are.
At Flipkart I keep the Lifestyle category's warehouses and dark stores from descending into chaos — pulling demand data, plugging price-parity holes, and basically making sure the right kurta ends up in the right pin-code before someone tweets about it.
When I'm not staring at dashboards, I'm wrangling F1 datasets, learning German (badly), Dutch (very badly), and Polish (catastrophically), and pretending FC Barcelona will win La Liga again any day now.
PowerShell pulls F1 data from Kaggle into SQL Server, a staging layer scrubs it clean with TRY_CAST and COALESCE, and Power BI tells you which of 770+ drivers and 300+ teams actually deserved their podiums. Built mostly because I had opinions.
30 days of session data, four funnel stages, a 4-pane Plotly dashboard, and a multi-page Power BI report powered by enough DAX to make your CPU sweat. Answers the eternal question: where do shoppers ghost us?
3,900 purchases cleaned with median imputation, segmented in PostgreSQL, then served back as a Power BI report showing a 27% subscription rate and a $59.76 average basket. Turns out customers are weirdly predictable.
A running log of what's on my desk, what I've finished, and what's queued up next. Covers pulled live from Open Library.
Always up for a chat about supply chain, F1 strategy, learning languages, or whether Messi was robbed of another Ballon d'Or. Hit me up on one of these.
