Top 17
Prep plan
Updated weekly · Last refresh Sep 20
P

Priceline Data Scientist Interview Questions

The questions to prepare for a Priceline Data Scientist interview. Questions from real interview reports rank first. Updated daily.

17questions
~2htotal time
Track your progressSign up free to work through all 17 questions and resume where you left off.
Start practicing free →
1
Product SenseStart here. 3 questions · ~25 min
Balance Revenue and User ExperienceEasy

Approach for balancing monetization with user experience in a product decision.

User NeedsValue PropositionProduct VisionPPriceline
Travel Recommendations SystemMedium

Tests ability to design a recommendation system for travel booking personalization at scale.

product designRecommendation SystemsPPriceline
More Product Sense questions with a free account
2
Metrics3 questions · ~25 min
Analyze New Feature EngagementMedium

Assess a new feature using adoption, activation, repeat usage, and retention metrics tied to user value.

Leading IndicatorsA/B TestingEngagement MetricsPPriceline
First Checks for Metric DropsEasy

Outline the first checks to diagnose a sudden drop in a core product metric, starting with data quality, scope, and decomposition.

Lagging IndicatorsLeading IndicatorsDiagnosisPPriceline
More Metrics questions with a free account
3
A/B Testing & Experimentation4 questions · ~33 min
Common Pitfalls in Experiment ResultsHard

Identify the main pitfalls that can distort A/B test interpretation and explain how to guard against them.

PeekingNovelty EffectSample Ratio MismatchPPriceline
Interpreting A/B Test DivergenceMedium

Assesses your approach to interpreting A/B test results under metric divergence.

A/B TestingPPriceline
More A/B Testing & Experimentation questions with a free account
4
Behavioral & Leadership4 questions · ~33 min
More Behavioral & Leadership questions with a free account
5
More topics3 questions · ~25 min
Statistical Tools for User AnalysisEasy

Explain the main statistical tools used to analyze user data and when each is appropriate.

RegressionCorrelationHypothesis TestingPPriceline
RANK vs DENSE_RANK in LeaderboardsEasy

Explain how RANK() and DENSE_RANK() handle ties differently in ordered SQL results such as leaderboards.

Window FunctionsRankingData WranglingPPriceline
More questions with a free account

Sign up to see every question

Create a free account to unlock this list and practice real interview questions.

Get my prep plan
Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
The finish line: interview-readyComplete all 17 questions plus 3 hands-on drills to finish this plan.