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Yelp interview notes, page 1 of 2

Large Enterprises

Screna has 18 Yelp interview write-ups. The most reported round is the product sense round (7).

18 interview notes · updated Jul 2026

Yelp·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Yelp product interview with a meaty KPI question focused on the Businesses side of the platform. One question, but it had a lot of surface area to cover.
  • For Yelp's business-facing product, what are the most important KPIs and how would you rank them in priority order? Walk through your reasoning.

“This one is deceptively wide.”

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Yelp·Product Manager·Hiring Manager Screen

Apr 2026
Interviewed for a PM role at Yelp and got a question about experimentation fundamentals. Pretty short round, felt more like a screen than a deep dive.
  • What is the purpose of having a control group in an experiment?

“Seemed basic but I second-guessed myself mid-answer.”

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Yelp·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
One product strategy question for a PM role at Yelp. Short and sharp, not much to say about the process itself.
  • How would you approach expanding Yelp into Asian markets?

“My first instinct was to just talk about localization and language support, which in hindsight was way too shallow.”

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Yelp·Software Engineer·Onsite - Product Sense / Strategy

Apr 2026
Yelp PM interview with a product sense question focused on their business-facing product. Not a lot of context to go on, but the question itself is a pretty meaty one if you've actually used Yelp for Business before.
  • You're the PM for Yelp for Businesses. What improvements would you prioritize and what's your reasoning?

“This is the kind of question where you can really sink yourself by going too broad.”

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Yelp·Data Scientist·Technical Phone Screen

Apr 2026
Yelp data science interview with a meaty A/B testing case built around redesigning a disliked social app feature. The whole question was basically one long multi-part problem that kept going deeper the more you answered.
  • Pick a consumer app feature you dislike and define a single or composite metric to measure how users respond to a proposed change.
  • How would you estimate the required sample size for the A/B test, and how long should the experiment run? Walk through your assumptions and calculations.
  • Which user segment or geography would you target first for this test, and what's your reasoning?
  • What statistical test would you use to compare the control and treatment groups, and why is it the right choice here?
  • The overall test result is not statistically significant, but the treatment group shows higher engagement. How do you interpret this, and do you (a) fully launch, (b) rerun or extend the test, or (c) dig into a specific subgroup like younger users?

“I went with Instagram's suggested posts in the home feed, which felt like a safe pick.”

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Yelp·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
PM interview at Yelp that came down to a metrics question. Pretty focused, nothing sprawling.
  • What are the most important metrics for Yelp?

“I went straight for review volume and business listings growth, which felt safe but maybe too obvious.”

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Yelp·Data Scientist·Onsite - System Design / Architecture

May 2026
Brutal system design round at Yelp for a data scientist role. The scope was enormous and I kept second-guessing my design choices out loud, which probably didn't help.
  • Design a personalized news feed system that supports both push and pull delivery at scale (100M monthly active users, 200k writes per second, 2M reads per second, p99 latency under 200ms).
  • How would you handle fan-out-on-write versus fan-out-on-read for a feed system, and what drives that decision?
  • Walk through the external API design for this system, including endpoints for publishing, subscribing, retrieving a feed with pagination, acknowledging consumption, retracting content, and logging feedback. Include request/response schemas and explain how you'd handle idempotency.
  • How would you implement deduplication, content diversity, freshness constraints, and daily notification caps in a feed ranking system?
  • Describe how you would build the ranking feature pipeline and serve online inference at low latency for a personalized feed.
  • How would you run online experiments on feed ranking while maintaining user-level traffic consistency and ensuring safe rollouts?
  • How would you handle GDPR deletion requests, multi-region replication, abuse and spam controls, and failure modes like partial regional outages in this system?

“The scale numbers threw me a bit.”

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Yelp·Product Manager·Onsite - Product Sense / Strategy

May 2026
Yelp product design interview, one question about building a scheduling product for their home services vertical. Pretty open-ended, not much else to go on.
  • Design a scheduling product for Yelp Home Services.

“This is the kind of question that sounds focused but opens up fast.”

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Yelp·Product Manager·Hiring Manager Screen

May 2026
Interviewed at Yelp for what seemed like a product or UX research adjacent role. One question about user testing methodology, pretty standard stuff but it made me realize I hadn't thought carefully about how I actually talk about mixing qual and quant work.
  • Walk me through your experience with user testing. How do you approach collecting both quantitative and qualitative data?

“I fumbled the structure a bit.”

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Yelp·Product Manager·Onsite - Cross-functional / Panel

May 2026
Yelp cross-functional interview with one question that was basically the whole conversation. Pretty standard PM behavioral setup but they pushed hard on the specifics of how I worked with engineers, not just what the outcome was.
  • Walk me through a project where you collaborated closely with an Engineering team. What was your decision-making process and how did the back-and-forth with engineers actually play out?

“I had a solid example ready but underestimated how much they'd dig into the process rather than the result.”

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