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TikTok interview notes, page 18 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·Recruiter / HR Screen

Jun 2026
Interviewed for a SWE role at TikTok. Just the one question from what I can tell, pretty standard motivation stuff.
  • Why do you want to work at TikTok?

“Gave the usual answer about scale and impact.”

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TikTok·Software Engineer·Technical Phone Screen

Jun 2026
TikTok data engineer interview with a coding problem focused on array partitioning. Pretty lean on context but the problem itself had some interesting edge cases worth thinking through.
  • Given an array of integers, split it into subarrays such that each subarray has an equal sum.

“My first instinct was prefix sums, which got me somewhere but I fumbled explaining the partition logic cleanly.”

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TikTok·Data Scientist·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round for a Data Scientist role at TikTok. The cross-functional alignment question was the centerpiece and it was heavier than I expected for what I thought would be a softer round.
  • Tell me about a time you had to work across multiple stakeholders with competing priorities. How did you get everyone aligned and still ship the project?

“I had a decent story ready but I fumbled the middle part where I should've explained how I actually resolved the trade-offs.”

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TikTok·Software Engineer·Technical Phone Screen

Jun 2026
TikTok software engineering interview with a classic sliding window / divide-and-conquer string problem. Nothing too exotic but the follow-up complexity questions kept it from being a pure grind-and-go.
  • Given a string and an integer k, find the length of the longest substring where every distinct character appears at least k times. Walk through your algorithm, justify its correctness, analyze time and space complexity, and cover edge cases like k=1, k larger than the string length, and all-unique-character strings.

“I went with divide and conquer.”

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TikTok·Software Engineer·Technical Phone Screen

Jun 2026
TikTok software engineer coding round, one question the whole time. Pretty standard binary search territory but the O(log n) constraint is what makes it interesting, you can't just linear scan and call it a day.
  • Given a sorted integer array and a target value, return the first and last positions of the target in the array. Must run in O(log n) time. Return [-1, -1] if the target isn't found.

“The naive approach jumps to mind immediately and that's the problem.”

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TikTok·Data Scientist·Technical Phone Screen

Jun 2026
TikTok data scientist interview that went deep into causal ML territory. One big multi-part question covering the full pipeline from learner selection to A/B testing the final policy. Felt more like a research defense than a standard DS interview.
  • You have observational data from an always-on promotion and want to target users to maximize incremental revenue. Walk through a causal ML approach to estimate heterogeneous treatment effects and derive a targeting policy, covering: choice of meta-learner and why, model and cross-fitting setup, handling positivity violations, evaluation metrics including off-policy estimation, fairness constraints on the policy, and how you'd safely A/B test it before full rollout.

“This was basically a dissertation prompt disguised as an interview question.”

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TikTok·Software Engineer·Technical Phone Screen

Jun 2026
Two coding problems back to back for a TikTok SWE screen. Linked list manipulation and a binary tree deletion with a specific reconnection rule. Nothing too crazy but the second one had enough edge cases to slow me down.
  • Given the head of a singly linked list and an integer n, remove the nth node from the end of the list and return the new head. Aim for a single pass with constant extra space.
  • Given the root of a binary tree (not a BST) and a key value, delete the node matching that key using this rule: find the deepest rightmost node in the tree, copy its value into the target node, then remove that deepest rightmost node. Return the new root.

“Two-pointer approach, pretty standard.”

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TikTok·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
TikTok coding round focused entirely on one data structure problem that sounds straightforward until you actually try to implement it correctly under pressure. The duplicate-handling requirement is where things get interesting.
  • Design a data structure that supports add(x), remove(x), and getRandom() all in average O(1) time, where duplicate values are allowed and getRandom must return each element with probability proportional to how many times it appears.

“I started with a hashmap and felt pretty good about it until they asked about getRandom.”

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TikTok·Data Scientist·Technical Phone Screen

Jun 2026
TikTok data scientist interview with a machine learning case question centered on churn prediction. Pretty standard stuff if you've done this type of modeling before, but there's more to unpack than it looks.
  • You need to build a churn prediction model for a subscription app. What modeling approaches would you consider, and how would you handle class imbalance and pick the right evaluation metrics?

“I started with logistic regression as a baseline because it's fast and interpretable, then moved into tree-based models like gradient boosting.”

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TikTok·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
PM interview at TikTok, got a estimation question about the social graph. Pretty niche angle for a product role but I guess they care a lot about how you reason through platform data.
  • Estimate the number of mutual follows the average TikTok user has.

“I started with DAU, then tried to segment users by how active they are since a casual lurker and a creator have wildly different follow graphs.”

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