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TikTok interview notes, page 27 of 28

Large Enterprises

Most of these TikTok write-ups come from Data Scientists (111), then Software Engineers (102) and Product Managers (35). The most reported rounds are the technical phone screen (167), the product sense round (33), the system design round (25) and the behavioral / leadership round (21).

279 interview notes · updated Sep 2026

TikTok·Software Engineer·Technical Phone Screen

Jul 2026
Interviewed for an SRE intern role at TikTok and got hit with a LeetCode hard in a 30-minute live coding session. First ever technical interview and it did not go well.
  • Implement a basic calculator that supports addition, subtraction, multiplication, division, and nested parentheses (LeetCode 772 style).

“I froze.”

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TikTok·Data Scientist·Technical Phone Screen

Jul 2026
TikTok Data Scientist SQL round, one question but it was a beast. The kind of problem where you think you understand it after the first read and then realize you missed three edge cases by the second.
  • Write standard SQL (no procedural code) to compute each user's total valid usage minutes for a specific date. You need to clip activity intervals to that day's boundaries, merge overlapping or adjacent intervals per user, then check whether any gap between consecutive merged intervals exceeds 60 minutes. If any such gap exists, return NULL for that user's usage. Otherwise return the total merged duration in whole minutes (floor).

“The clipping part I got pretty quickly, GREATEST and LEAST to bound start and end to the day window.”

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TikTok·Software Engineer·Technical Phone Screen

Jul 2026
TikTok software engineering interview that centered on a graph theory problem. Pretty standard algorithmic round but the follow-up questions about edge cases and complexity analysis kept it from being a cakewalk.
  • You're given an undirected graph as an adjacency list where adj[i] contains the indices of guests who know guest i. Can all guests be seated in at most two groups such that no two guests in the same group know each other? Return true or false, implement the algorithm, handle disconnected components, and analyze time and space complexity.

“This is bipartite checking, which I recognized pretty fast, but I fumbled the disconnected components part initially.”

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TikTok·Software Engineer·Technical Phone Screen

Jul 2026
TikTok software engineering interview that went pretty deep into Python internals. Three questions, all technical, no fluff. Felt like they wanted to see if you actually understood the language or just knew how to use it.
  • In Python, what is the difference between mutable and immutable objects, and how does that distinction affect what happens when you pass them into functions or store them in containers?
  • How does a shallow copy differ from a deep copy in Python, and when would you use one over the other? What can go wrong with nested structures?
  • Can you explain Python's Global Interpreter Lock, how it affects multithreading versus multiprocessing, and when you'd choose threads, processes, or async I/O for a given workload?

“This sounds basic until you're mid-explanation and realize you're not totally sure how to describe what happens when you pass a mutable default argument to a function.”

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TikTok·Data Scientist·Technical Phone Screen

Jul 2026
TikTok Data Scientist interview that went deep into classical AI search algorithms. More graph theory than I expected for a DS role, but looking back it makes sense given how much recommendation and ranking work they do.
  • Given a weighted graph with nodes S, A, B, C, D, G and specific edge weights, trace the node expansion order and final path found by BFS (treating edges as unweighted), uniform-cost search, and A* with the provided heuristic values. Break ties alphabetically.
  • Prove whether the given heuristic h is admissible and consistent for the provided graph.
  • Compare the time and space complexity of DFS, BFS, UCS, and A* in terms of branching factor b and depth d. Describe a scenario where DFS wins on memory but fails to give an optimal solution.
  • Under what condition does A* reduce to Dijkstra's algorithm? Illustrate using the heuristic values provided.

“This is where I spent most of my mental energy.”

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TikTok·Software Engineer·Onsite - System Design / Architecture

Jul 2026
TikTok system design round, one massive question that basically covered every angle of a flash-sale ticketing system. The scope was genuinely intimidating and I left feeling like I'd only scratched the surface on half the topics.
  • Design a high-concurrency ticketing system for limited inventory (like a sold-out concert) that can handle millions of simultaneous purchase attempts without overselling. You need to cover admission control, inventory correctness, bot mitigation, idempotency, hot-key sharding, APIs, data modeling, caching, async messaging, consistency tradeoffs, failure handling, capacity planning, and monitoring.

“This was essentially thirteen questions wrapped in one.”

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TikTok·Software Engineer·Technical Phone Screen

Jul 2026
Coding interview at TikTok for a software engineer role. Two algorithm questions, both with follow-up discussions on complexity and design trade-offs. Pretty standard competitive programming territory but the extensions they asked about kept things interesting.
  • Given a binary grid where 1s are land and 0s are water, count the number of distinct island shapes. Two islands count as the same only if one can be translated to match the other; rotations and reflections are considered different. Then explain how you'd extend this if rotations and reflections also made islands equivalent.
  • Given an integer array and a window size k, find the maximum value in every contiguous subarray of length k. Implement a linear time solution and explain why it's O(n). Then compare it to a heap-based approach and discuss the trade-offs.

“The base version I got through fine.”

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TikTok·Data Scientist·Onsite - Behavioral / Leadership

Jul 2026
TikTok data scientist interview with a meaty behavioral question that was way more structured than I expected. They really wanted you to have lived this, not just theorized it.
  • Tell me about a time you disagreed with a partner team over a product direction and still drove the work end-to-end. Walk through the decision you proposed, the metrics you used to define success (baseline, expected lift, acceptable regression), how you structured the rollout or experiment, how you handled cross-timezone coordination, and one trade-off you consciously accepted.

“This question is doing a lot of heavy lifting at once and I underestimated it.”

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TikTok·Data Scientist·Technical Phone Screen

Jul 2026
TikTok data scientist interview with a stats-heavy question about comparing creator behavior across cohorts. Pretty technical, felt like they wanted to see if you actually know when to use which test rather than just naming tools.
  • After computing cohort-level posting metrics, how would you determine whether posting patterns differ across cohorts? Walk through the metrics, visualizations, and statistical tests you'd use, and explain what would drive your final conclusion.

“I started with the visual layer, retention curves overlaid per cohort, average posts per user over time, that kind of thing.”

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TikTok·Data Scientist·Technical Phone Screen

Jul 2026
TikTok data scientist interview, technical phone screen or onsite SQL round. One meaty query question that looked straightforward until I started counting all the edge cases they wanted handled.
  • Using ad delivery logs, write a SQL query to find advertisers whose CTR dropped by at least 20% in the most recent 7-day window compared to the prior 7-day window. Exclude flagged suspicious ads, enforce a minimum impression threshold of 10,000 per window per advertiser, handle missing days as zero, guard against division-by-zero and integer division, and return advertiser_id, both CTRs, and the relative drop ordered by drop descending.

“This one had way more moving parts than it looked.”

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