Zepto · Senior Product Analyst
Bengaluru · Nov 2024 · 4 views
✓ Offer acceptedTotal process: 10 days
5 rounds: →→→→
This experience is over 18 months old. Interview processes change — use it for general patterns, not specifics.
I have about 5.5 years of experience as a Senior Business Analyst at an e-commerce product company. I applied for a Senior Product Analyst role on Zepto's Last Mile team in Bengaluru in November 2024.
I came in through a referral — someone who knew about the opening at my level put me forward. I think what got me shortlisted was the domain overlap: product analytics in e-commerce maps cleanly onto quick-commerce work.
I prepped for about a week, though fairly lightly. In hindsight, I spent that week on the wrong things — more technical practice when the loop was actually much more about structured problem-solving and case studies.
| When | Stage |
|---|---|
| Nov 2024 | Referred for the role |
| — | Round 1 — Screening · phone · ~15–20 min · cleared |
| — | Round 2 — Data Handling + Guesstimate · video · ~45 min · cleared |
| — | Round 3 — SQL Joins + Project Deep-Dive · virtual · ~45 min · cleared |
| — | Round 4 — Case Study + Experiment Design · onsite · ~1 hr · cleared |
| — | Round 5 — HRBP Closeout · onsite · ~15 min · cleared |
| After 3 days | Offer received · ₹30–40 LPA · accepted |
Format: Phone | Duration: ~15–20 min
A conversational screen with the recruiter. They walked through my current experience and the areas my projects covered.
Topics covered
Verdict: Cleared
Format: Video | Duration: ~45 min | Interviewer: Lead Product Analyst
Two SQL questions first, then a guesstimate, then time for my questions.
DENSE_RANK, ROW_NUMBER, and RANK.They framed it around a class of students with marks across different subjects, and had me reason through how each function would number/rank rows differently — especially how ties are handled and whether ranks skip.
table_a with rows 1,2,3,4,5 and table_b with rows 1,2,2,3,3,3,4,4,5,6, what does SELECT a.* FROM a JOIN b WHERE 1=1 return?table_a
a
1
2
3
4
5
table_b
b
1
2
2
3
3
3
4
4
5
6
SELECT a.* FROM a JOIN b WHERE 1=1; -- cross join: 5 × 10 = 50 rows
The trick: there's no join condition — WHERE 1=1 is always true — so it's effectively a cross join, and every row of a is repeated once per row of b. I asked for a moment, worked through it, and got there.
I bifurcated the country by city tier, then layered in income parity and population density per tier. I initially anchored on existing quick-commerce order demand as a reference, but they asked me not to assume that — so I pivoted to demand patterns of leading supermarkets and superstores as a proxy instead. I kept it a discussion throughout, checking each hypothesis with the interviewer rather than monologuing, and closed by asking what the day-to-day of the role looked like.
Where I got stuck: The cross-join question — a brief pause before it clicked. On the guesstimate, the interviewer was actively collaborative on the hypotheses.
Verdict: Cleared
Format: Virtual | Duration: ~45 min | Interviewer: Associate Director, Product Analytics
SQL exercise
Project deep-dive
I picked the project I felt added the most value: a detailed analysis I'd done to estimate whether the buffer applied to delivery lanes was optimally sized. We went deep on the metrics I tracked and the teams and people I'd worked with to land it.
Verdict: Cleared
Format: Onsite | Duration: ~1 hr (scheduled 45 min) | Interviewer: Director, Product
My approach:
Then they pushed: how would I handle network impact? I didn't have an immediate answer — I suggested comparing similar stores, similar cities, and similar time frames. The interviewer asked whether I understood time-slicing experiments. I didn't. He walked me through the concept and we discussed how it would help neutralise network effects.
Where I got stuck: The network-impact question and not knowing time-slicing. The interviewer was generous about it and turned it into a teaching moment rather than a gotcha.
Verdict: Cleared
Format: Onsite | Duration: ~15 min
A short conversation about the company's expectations from me and what I should expect from the role. More alignment than evaluation.
Verdict: Cleared
I received an offer three days after the final round and accepted it. The whole loop ran to roughly 10 days start to finish — impressive given it spanned Diwali week. The package was in the ₹30–40 LPA range.
I'd spend the prep week studying how to structure case studies rather than on technical practice. I over-invested in the technical side — the SQL was never the hard part — and under-invested in problem-solving frameworks. The bar here is about thought process, not query syntax.