Expedia data scientist interviews, as candidates describe them, combine behavioral conversations, SQL, a case study, and in one report LeetCode-hard coding on HackerRank. Here is what to prepare, with reported questions.
$156K
Avg. Base Comp
$191K
Avg. Total Comp
4-5 rounds
Typical Rounds
Not reported
Process Length
Three candidates describe Expedia data scientist interviews, and the formats differ, so prepare for range rather than one script. All three mention a hiring manager conversation with behavioral content, and each also reports SQL or other technical testing.
One candidate reports four rounds after a recruiter call: a hiring manager round, a technical round on SQL, Python and A/B testing, a product sense case study with a panel, and a final product and stakeholder round. That candidate advises tying your experiences back to Expedia's principles and recalls questions such as the most complex problem you have worked on and a problem involving diverse viewpoints.
Another candidate describes a hiring manager phone screen with basic SQL, followed by four thirty-minute interviews and a take-home case study presented live. That candidate also reports two HackerRank coding interviews, one at LeetCode hard level, so practice algorithms as well as SQL and ML basics.
A third candidate, interviewing for an advertising-focused role, reports a recruiter screen, a behavioral hiring manager round, a panel with a product manager and an advertising manager, and a technical final round on SQL (including window functions such as LAG), Tableau, and conceptual machine learning. Their standout question asked how to choose between a more relevant hotel that bids less and a less relevant hotel that bids more for limited ad space. If your team touches advertising, rehearse the revenue versus relevance trade-off.
One candidate reported waiting about ten days for a response after the final interview, so plan for possible delays.
Synthesized from 4 candidate reports by our editorial team.
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Real interview reports from people who went through the Expedia, Inc. process.
Total 4 rounds not including recruiter round -
Questions asked: Important to tie back all your experiences and what you could do better with their principles. eg: Tell me about yourself? What's the most complex problem you've worked on? Whats's the most diverse viewpoint problem statement have you worked on?
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Expedia, Inc.
How would you assess the validity of the result?
| Question | |
|---|---|
| Random SQL Sample | |
| Permutation Palindrome | |
| Bagging vs Boosting | |
| Completed Shipments | |
| Revenue Retention | |
| Average Commute Time | |
| Significance Time Series | |
| Average Ride Duration | |
| Google Maps Improvement | |
| Nearest Common Ancestor | |
| Groups of Anagrams | |
| Xgboost vs Random Forest | |
| Target Indices | |
| Hurdles In Data Projects | |
| Average Revenue per Customer | |
| Lasso vs Ridge | |
| Forecasting New Year Revenue | |
| Count Transactions | |
| Banner Ad Strategy Success | |
| Implementing the Fibonacci Sequence in Three Different Methods | |
| Bias vs. Variance Tradeoff | |
| Data Preparation for Imbalanced Data | |
| Shoe Demand Seasonality | |
| String Palindromes | |
| Best Performing Advertisers | |
| Deciding Between Solutions | |
| Check Matching Parentheses | |
| Increase Search Ads | |
| Client Solution Pushback |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report an opening conversation with a recruiter and a hiring manager. Reported topics include role expectations, projects, why Expedia, failures and recoveries, and communicating findings to non-technical stakeholders. One candidate also saw straightforward SQL questions at this stage.
Candidates report SQL (subqueries and window functions like LAG), Python, A/B testing, Tableau, and conceptual machine learning. One candidate reports two HackerRank coding interviews with LeetCode-hard difficulty, so the coding bar may vary by team or loop.
One candidate describes a product sense case study with a panel, and another a take-home case study presented during an interview. An advertising-focused candidate faced a panel with a product manager and an advertising manager, including an ad auction trade-off question.
One candidate reports a final round focused on product and stakeholder topics, with behavioral and experience-based questions. Candidates may be asked to tie past experience to Expedia's principles, including complex problems and diverse viewpoints.
