Yelp has used HackerRank-style technical screens for software and machine-learning roles. The assessment depends on the role and is not guaranteed for every experienced candidate. Practical examples emphasize data modeling, string processing, ranking, and test construction.

Use the invitation to confirm the language, time limit, and whether the task is automated or paired with an interviewer.

When to Expect the OA for Your Role

Internship and entry-level tracks are the most likely to include an online screen immediately after application review. Applicants to experienced software developer roles might have a recruiter call before a live coding screen. For machine learning roles, the assessment might include a general coding screen with statistics or data-related questions. Check the job description to confirm the scope.

Does Your Online Assessment Matter?

The technical screen is an important step in determining who advances. Yelp does not publish a company-wide cutoff. Correct output, a readable model, and meaningful tests all matter. Business-focused prompts often include duplicate records, tie-breakers, or ambiguous IDs, so parse the requirements carefully.

Compiled List of Yelp OA Question Types

These problems cover prefix search, frequency ranking, randomized selection, string segmentation, and local business data modeling.

1. Design Search Autocomplete System - prefix search and ranked suggestions.
2. Top K Frequent Words - sorting with lexical ties.
3. Insert Delete GetRandom O(1) - indexed random selection.
4. Random Pick with Weight - prefix weights and sampling.
5. Word Break - dynamic programming.
6. Group Anagrams - normalized grouping keys.
7. Merge Intervals - ordered interval merging.
8. Design HashMap - explicit key-value storage.
9. LeetCode problem 682 - Find Duplicate File in System - parsing and grouping structured records.
10. Accounts Merge - finding entities in a dataset using connected components.

Yelp Interview Questions

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How to Prepare and Pass the Yelp Online Assessment

Use four focused sessions: practice a trie/prefix index, a frequency-ranking problem with deterministic ties, a structured record parser, and one timed mixed mock. Write tests for duplicates, empty collections, stable ordering, and equal scores. If the prompt involves business objects, define each object's identity separately from its display name and choose map keys accordingly.

For machine learning roles, add one more practice block for probability and tests of nondeterministic behavior. Use Lodely to keep Yelp coding, system design, and behavioral questions together as you prepare for later interviews.

Yelp Interview Question Breakdown

Design Search Autocomplete System

Type: Prefix search and ranking. Prompt: Return relevant stored terms as the user searches. Approach: Keep retrieval and tie-breaker rules deterministic. What It Tests: Data modeling, tries, and ranked output.

Top K Frequent Words

Type: Frequency counting and ordered selection. Prompt: Return the most common terms with a defined tie rule. Approach: Sort by frequency and lexical order in different directions. What It Tests: Comparator design and complexity choices.

What Comes After the Online Assessment

Later stages of a Yelp interview might include live coding, product or system design, project discussions, and behavioral interviews. Machine learning roles may also include questions about statistics and model design. Explain your test cases and why each matters. Live interviewers often ask candidates to extend a working solution.

Conclusion

Use precise modeling and deterministic results, especially for business data. Use Lodely to prepare for a live Yelp interview.