TikTok Interview Questions — Page 17

TikTok·Data Scientist·Technical Phone Screen

Jun 2026

TikTok data science interview with a brutal SQL question covering funnel analysis, drop-off detection, and rolling windows all in one shot. The schema was manageable but the requirements kept stacking up in ways that made it hard to stay organized under pressure.

Write PostgreSQL to analyze a 4-step shopping funnel (view_product, add_to_cart, checkout_start, purchase) across multiple tables. For each country and event date, compute step-to-step conversion rates after deduplicating to the first occurrence per user, session, and product, and only counting a conversion if both steps appear in timestamp order within the same user-session-product group.
For each user in a given month, identify their most frequent drop-off step across sessions, where a drop-off means the last funnel step reached without the next step occurring in the same session or within 24 hours by the same user and product. Also compute the median elapsed time from the prior step to that drop-off across their sessions.
For each day in a given month and by country, compute a 7-day rolling conversion rate from add_to_cart to purchase. The denominator is unique user-product add_to_cart events on day D, and the numerator is the subset where the same user and product has a purchase event within 7 days after the add_to_cart timestamp, across any session.

“This took me way longer than it should have.”

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TikTok·Data Scientist·Technical Phone Screen

Jun 2026

TikTok Data Scientist interview with a greedy algorithm problem centered on budget optimization. Pretty straightforward once you see the pattern, but I fumbled around longer than I should have before landing on the right approach.

Given a customer's budget and a list of product prices, how would you design an algorithm to maximize the number of distinct products the customer can buy without exceeding the budget?

“Spent the first few minutes overcomplicating it.”

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TikTok·Product Manager·Onsite - Product Sense / Strategy

Jun 2026

TikTok PM interview with a content moderation prioritization question. Pretty focused session, one meaty product strategy problem and not a lot of fluff around it.

How would you prioritize features in a content moderation tool?

“I went straight to user harm reduction as the north star and tried to bucket features by severity of the problem they solve.”

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TikTok·Machine Learning Engineer·Technical Phone Screen

Jun 2026

TikTok ML Engineer interview with a dynamic programming problem. Pretty standard coding round but the constraints were tight enough that a naive solution would've timed out, so you had to think about efficiency from the start.

Given a string and a dictionary of words, determine whether the string can be fully broken down into a sequence of valid dictionary words. Words can be reused.

“My first instinct was recursion, which technically works but blows up on longer inputs.”

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TikTok·Product Manager·Onsite - Product Sense / Strategy

Jun 2026

Interviewed for a PM role at TikTok and got hit with a feature prioritization question. Pretty open-ended, which I wasn't fully ready for.

Which TikTok features would you prioritize for improvement, and how would you go about improving them?

“I went straight to the For You feed because it felt obvious, and I think that was a mistake.”

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TikTok·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026

Interviewed for a data engineering role at TikTok, which ended up being a mix of technical depth and behavioral questions that felt more like a government contractor screen than a typical tech company loop. The USDS angle threw me a bit since I wasn't expecting public-sector framing from TikTok.

Walk me through a data engineering project you're proud of, focusing on your role, the technical decisions you made and why, and what the measurable impact was.
Describe a production data issue you had to debug under pressure. What broke, how did you figure it out, and what did you put in place afterward?
Tell me about a time stakeholders changed the timeline on you last minute. How did you handle the shift, keep people informed, and reset expectations?
Why do you want to work on a public-sector data team, and what would you focus on in your first 90 days?

“I picked a pipeline migration project and tried to hit all the angles: what I owned, why we chose the architecture we did, what we gave up to get there.”

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TikTok·Data Scientist·Hiring Manager Screen

Jun 2026

Pretty standard intro round for a Data Scientist role at TikTok. Nothing technically demanding, just the usual background walkthrough and resume deep-dive.

Tell me about yourself and walk me through your career so far.
Which projects on your resume had the most meaningful business impact, and how did they play out?

“I'd done this a hundred times but still fumbled the pacing.”

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TikTok·Product Manager·Recruiter / HR Screen

Jun 2026

Interviewed for a PM role at TikTok, pretty standard behavioral screen with one question that felt like a warmup but still tripped me up a bit.

Do you thrive in fast-paced work environments?

“Answered yes and rattled off a couple examples but halfway through I realized I was just listing things without actually showing adaptability.”

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TikTok·Software Engineer·Technical Phone Screen

Jun 2026

TikTok software engineer coding round with two LeetCode-style problems. Both were on the harder side and the follow-up on the first one added a wrinkle I didn't fully see coming.

Given a message string and a per-character width limit, split the message into numbered parts where each part includes a suffix like '<1/8>', '<2/8>', etc. Follow-up: the suffix itself must be counted toward the width limit.
Given an m x n candy board, repeatedly remove all horizontal or vertical runs of 3 or more identical candies, apply gravity to drop remaining candies down, and return the board once it stabilizes.

“The base version isn't too bad once you figure out the suffix length math.”

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TikTok·Data Scientist·Technical Phone Screen

Jun 2026

TikTok data scientist interview that went deep into k-means from scratch, the kind of question where you think you know clustering until someone asks you to do it by hand with a specific seed and two full Lloyd iterations.

Given a specific set of 8 points in 2D space and k=2, walk through k-means++ initialization using a fixed random seed and Euclidean distance. Which centroids get sampled and why?
Perform two full Lloyd iterations by hand on the initialized centroids: assign each point to its nearest centroid (breaking ties by lower index), then recompute centroids. Show cluster memberships and centroid coordinates after each iteration.
Compute the SSE (sum of squared errors) after the second Lloyd iteration.
How would you implement k-means efficiently in NumPy without looping over points? What is the time complexity per iteration, and how do you handle empty clusters robustly?

“This part tripped me up more than I expected.”

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