Katkat

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Yelp interview questions

5 practice questions in the style of Yelp's interviews, covering Machine Learning, Analytics & Experimentation, Behavioral & Leadership, Coding & Algorithms.

Questions5

3 easy0 medium2 hard

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Yelp interview questions by the numbers

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Katkat has 5 Yelp interview questions. The largest topics are Analytics & Experimentation (40%), Behavioral & Leadership (20%) and Coding & Algorithms (20%). By difficulty: 60% easy and 40% hard. The most common round is Technical Screen (60%). Frequent concepts include A/B Testing, Statistics, Algorithms and Analytics.

Topics

Difficulty

  • Easy60% · 3
  • Hard40% · 2

Interview rounds

  • Technical Screen60% · 3
  • Onsite40% · 2

Roles

  • Data Scientist100% · 5

Frequent concepts

  • A/B Testing40% · 2
  • Statistics40% · 2
  • Algorithms20% · 1
  • Analytics20% · 1
  • Arrays20% · 1
  • Data Manipulation20% · 1

Most mentioned in interview experiences

  1. 1.Estimate Experiment Duration with Power Analysis1 report
  2. 2.Recommend a Decision After a Nonsignificant Experiment1 report
  3. 3.Return Integers in Descending Ranked Order1 report

Counted from 1 candidate interview experiences on Katkat. How we collect and count

Showing 1–5 of 5 results

  • Design a Cold-Start-Aware RecommenderHard

    This question evaluates a data scientist's expertise in production recommender systems, covering cold-start strategies, two-stage retrieval and ranking model design, multimodal feature engineering, exploration–exploitation, bias-corrected experimentation, and low-latency serving.

    YelpData ScientistMachine LearningOnsite
  • Estimate Experiment Duration with Power AnalysisEasy

    This question tests the ability to perform a power analysis to calculate sample size requirements for an A/B test and derive the experiment duration based on traffic constraints.

    YelpData ScientistAnalytics & ExperimentationTechnical Screen
  • Handle PM Ambiguity and Drive OutcomesHard

    This question evaluates leadership, stakeholder management, and incident response competencies within a data science context, including the ability to define measurable success metrics, negotiate scope under ambiguity, and make data-driven decisions during product regressions.

    YelpData ScientistBehavioral & LeadershipOnsite
  • Recommend a Decision After a Nonsignificant ExperimentEasy

    This question tests the ability to interpret nonsignificant experimental results and formulate data-driven business recommendations beyond simple hypothesis testing.

    YelpData ScientistAnalytics & ExperimentationTechnical Screen
  • Return Integers in Descending Ranked OrderEasy

    This problem tests the ability to manipulate lists and sort data while maintaining the relative order of duplicate elements using common programming patterns.

    YelpData ScientistCoding & AlgorithmsTechnical Screen

Yelp interview experiences

All 1 →
  • SQL, Python, and ExperimentationYelp · Data Scientist · Technical Screen · Aug 2026

    Overall, there were three parts: SQL, Python, and experimentation. SQL: the main focus They provide several table schemas. The first question starts with basic aggregation. You just need to use count(distinct ...) flexibly together with sensible filtering, so the key is to understand the table schemas carefully first. You can ask more questions. The second question generally tests a simple metric…

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