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Meta·Data Scientist·Onsite - Coding / Algorithms·Senior

Senior
Jul 2026

Summary

Meta onsite for a Data Scientist role, SQL-heavy with a focus on product event log analysis. The interviewer clearly wanted to see whether you actually know window functions or just know the word 'window functions'.

Questions Asked (1)

Q1

Given a table of user events with columns for date, user ID, event type, and timestamp, write a SQL query that returns the top three most active users by event count for each date, ordered by activity.

Product Analytics & MetricsAlgorithms & Data Structures
Author's notes

I knew ROW_NUMBER() was the move but fumbled the partition clause at first, wrote PARTITION BY user_id instead of PARTITION BY event_date and just stared at it for a second before catching myself.

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AI HintsAI Generated

Suggested Approach

Start by aggregating event counts per user per date using GROUP BY. Then use a window function like ROW_NUMBER() or RANK() partitioned by date and ordered by count descending to rank users. Finally, filter to top 3 ranks per date and order the output by date and rank.

Pro tip: Clarify tie-breaking rules upfront (e.g., if multiple users have the same count, use ROW_NUMBER for deterministic results or RANK if ties should be included). Also, mention that you'd validate the query on a small sample to ensure correctness.

1. Understand the data and requirements

Confirm the table schema, event types, and whether 'top three' means exactly three users per date or could include ties. Clarify ordering: by event count descending, then by user ID for determinism.

2. Aggregate event counts per user per date

Write a subquery or CTE that groups by date and user ID, counting events. Use COUNT(*) or COUNT(DISTINCT event_id) depending on whether duplicate events should be counted.

3. Rank users within each date

Apply a window function (ROW_NUMBER, RANK, or DENSE_RANK) over a partition by date, ordered by event count descending. Choose the function based on tie-handling requirements.

4. Filter to top 3 per date

Wrap the ranked result in an outer query and filter where rank <= 3. Ensure the final output includes date, user ID, event count, and rank.

5. Order the final result

Order by date ascending and rank ascending (or event count descending) to present the top users per date in a clear, readable format.

Key Points to Mention

  • Use of window functions (ROW_NUMBER, RANK, DENSE_RANK) for per-group ranking.
  • Handling ties: explain the difference between ROW_NUMBER (arbitrary tie-break), RANK (gaps after ties), and DENSE_RANK (no gaps).
  • Performance considerations: indexing on (date, user_id) and avoiding unnecessary sorting.
  • Correctness: ensuring the query returns exactly three users per date, even if there are fewer than three users on a date.
  • Edge cases: dates with fewer than three users, null values, and duplicate events.
  • Readability: using CTEs for clarity and maintainability.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.