All experience

Industry

Product Intern

EAT.FIT
When
Sept 2021 – Dec 2021
Where
Bengaluru, India
across the citytwo streets away
Location polls keyed to distance left, sparse across town, dense near the door

Highlights4

  • Adaptive polling: cut driver-location serving cost 45% with poll intervals keyed to distance remaining, interpolated on the client so movement still looks continuous.
  • Live order tracking: a Google Maps screen with route polylines and an ETA recomputed on every fix, shipped during a quarter of 25% user growth.
  • Notification service: WebSocket and Express.js with backpressure-aware fan-out and duplicate-safe reconnection; after launch, reported CSAT rose 28% and support volume fell 35%.
  • Competitor data: a Python scraping toolchain pulling catalogs and reviews into the analytics warehouse on a schedule, normalized to one schema.

More detail

All 5 points

Order tracking

  • Interpolated between location samples on the client so a slower poll still renders as continuous movement, which is what made the cost reduction invisible to the user.
  • Kept the map honest under a stale fix: the marker holds its last known position with the timestamp shown rather than drifting toward a guess.

Notifications

  • Made reconnection safe: exponential backoff plus a per-message id, so a socket that drops mid-delivery resumes without sending the same notification twice.
  • Wrote the degraded path deliberately: when the socket is unavailable the client falls back to polling rather than going silent, because a missed order update is a support ticket.

Data

  • Automated competitor-catalog harvesting with a Python scraping toolchain, pulling catalogs and reviews into the analytics warehouse on a schedule, normalized to one schema so pricing, positioning and CX workflows read the same shape.

Tools

  • React.js
  • Google Maps API
  • Python
  • Node.js
  • Express.js
Next roleComputer Vision Researcher, DA-IICT