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Pinterest·Data Scientist·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Pinterest data scientist round, basically a coding problem about computing free time slots in a restaurant booking system. More algorithmic than I expected for a DS role, felt like it belonged in a software eng loop.

Questions Asked (1)

Q1

Given a restaurant's opening hours and a list of existing reservations per day, write a function that returns the available time intervals for each day. Reservations may be unsorted or overlapping and should be merged before computing free slots.

Algorithms & Data StructuresAPI & IntegrationsSystem Design
Author's notes

My first instinct was to just iterate and subtract, which works until you have overlapping reservations and suddenly your logic is wrong.

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AI HintsAI Generated

Suggested Approach

First, clarify the input format and edge cases (e.g., time zones, overnight hours, reservation spanning multiple days). Then, for each day, merge overlapping reservations and compute free intervals by subtracting merged reservations from the opening hours. Finally, discuss time complexity and potential optimizations.

Pro tip: Mention that you would handle edge cases like reservations that start before opening or end after closing, and consider using a sweep line algorithm for efficiency if the number of reservations is large.

1. Clarify requirements and edge cases

Ask about input format (e.g., time representation, opening hours per day, reservation structure), and edge cases like overnight hours, reservations spanning multiple days, and time zones.

2. Design data structures and algorithm

Decide on data structures (e.g., list of intervals, priority queue) and algorithm: sort reservations by start time, merge overlapping intervals, then compute free slots by iterating through merged intervals and opening hours.

3. Implement and handle edge cases

Write code to merge intervals and compute free slots, ensuring to handle cases where reservations extend beyond opening hours or overlap with each other.

4. Analyze complexity and optimize

Discuss time complexity (O(n log n) due to sorting) and space complexity, and suggest optimizations like using a sweep line for large datasets.

5. Test with examples

Walk through a few test cases, including unsorted and overlapping reservations, to verify correctness and edge case handling.

Key Points to Mention

  • Merging overlapping intervals: sort by start time, then iterate and merge if next start <= current end.
  • Computing free slots: subtract merged reservations from opening hours, handling boundaries.
  • Edge cases: reservations outside opening hours, overnight hours, multiple days, empty reservations.
  • Time complexity: O(n log n) for sorting, O(n) for merging and computing free slots.
  • Data structures: use lists of tuples or interval objects, possibly a priority queue for streaming data.
  • Scalability: consider sweep line algorithm or interval trees for large number of reservations.

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