TikTok Interview Questions — Page 25

TikTok·Software Engineer·Technical Phone Screen

Jun 2026

TikTok software engineer coding round, one algorithmic problem on subarrays. Pretty straightforward premise but I fumbled around longer than I should have before landing on the right approach.

Given an array of positive integers, find a contiguous subarray of at least two elements where the sum of its minimum and maximum values is as large as possible. Return that maximum sum.

“My first instinct was to brute-force every subarray and track min/max as I expanded, which works but I spent too long second-guessing whether there was a smarter O(n) trick.”

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TikTok·Software Engineer·Onsite - System Design / Architecture

Jun 2026

System design round at TikTok for a software engineer role. One big open-ended question that sprawled into a bunch of sub-topics, felt more like a technical conversation than a structured interview.

Walk through the end-to-end architecture of a system you've built. For each component, cover how you'd optimize for performance, what QPS you'd expect, how Kafka ensures message delivery, and any other relevant design considerations.

“This one sprawled fast.”

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TikTok·Data Scientist·Technical Phone Screen

Jun 2026

TikTok data scientist interview with a SQL-heavy technical screen. The question was applied and scenario-based, not just 'write a join', which I appreciated but also didn't fully expect.

Given a page_views table and a purchases table for an e-commerce platform, write a SQL query that returns, for each month: the number of distinct visitors, the number of distinct purchasers, and the conversion rate. Then extend it to also include average order value per month.

“The core join wasn't bad but I tripped on the conversion rate piece.”

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TikTok·Data Scientist·Technical Phone Screen

Jun 2026

SQL round for a Data Scientist role at TikTok, two questions back to back. Nothing conversational, just schema and tasks. Felt more like a take-home but it was live.

Given a users table and a transactions table, write a query to find all users whose total completed crypto transaction volume exceeds £100 within the first 7 days of their account creation.
Using an activity table with view and click events, compute the click-through rate per product and return the product with the highest CTR. How do you handle products that have views but no clicks, or no views at all?

“The window logic is what gets you.”

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TikTok·Data Scientist·Technical Phone Screen

Jun 2026

TikTok data scientist interview focused heavily on experimentation design and causal inference. Two meaty questions back to back with no warmup, which felt a bit abrupt. The topics were squarely in the DS wheelhouse but the depth expected was real.

An A/B test changed a call-to-action button color from green to red and retention dropped. Walk through the diagnostics you'd run to figure out whether the result was driven by uneven traffic allocation or other experiment quality problems.
You need to measure the causal effect of receiving negative reviews on a merchant's coupon repurchase rate. What data would you need and what methodology would you use to get an unbiased estimate?

“I started with sample-ratio mismatch, which felt like the obvious first move, and they nodded along.”

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TikTok·Software Engineer·Technical Phone Screen

Jun 2026

First round technical screen for a backend SWE role at TikTok, and it was genuinely one of the stranger interviews I've heard of. The interviewer showed up with half her face visible on camera, skipped any introduction, grilled me hard on internship work I had limited context on, threw a LC Hard at me, and then refused to share anything about her own background when I asked. Ended with feedback that my project work was 'too shallow', which, sure, maybe, but the whole thing felt off.

Walk me through a project you worked on during your internship. Why did your team design the service the way they did?
Solve a LeetCode Hard level coding problem.

“This went sideways fast.”

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TikTok·Product Manager·Onsite - Product Sense / Strategy

Jun 2026

PM interview at TikTok that leaned heavily into trust and safety territory. Three connected questions all circling the same theme: cheating detection, prevention, and enforcement. Felt more like a product strategy case than a standard PM screen.

How would you detect cheating in an online game? Walk through the signals you'd track, how the data would flow, and what algorithms you'd use to flag bad actors.
Why do players cheat in the first place, and what product or policy changes could reduce that motivation?
Once you've identified cheaters, how do you enforce consequences? And if some users push back or feel wrongly penalized, how do you handle that?

“This one required more technical depth than I expected for a PM role.”

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TikTok·Data Scientist·Onsite - System Design / Architecture

Jun 2026

TikTok data scientist interview that went deep into streaming systems and experimentation infrastructure. One long technical question that basically covered six sub-problems back to back, which felt like a design session more than a traditional interview.

Design a streaming system that detects sample ratio mismatch across many concurrent experiments, using two partitioned input streams: one for experiment assignments and one for pageviews. The system needs to deduplicate per user per experiment using idempotent state, maintain rolling per-variant counts in O(1) memory while handling late events up to 24 hours, run a chi-square goodness-of-fit check every minute with Yates correction and alert when p < 1e-4 and the absolute difference is at least 0.3 percentage points, filter out bot-like users who receive too many assignments in a short window, and support horizontal sharding across workers.
How would you validate this SRM detector using historical data replay without leaking ground truth into the detection logic?

“This was a lot to hold in your head at once.”

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TikTok·Software Engineer·Technical Phone Screen

Jul 2026

Frontend coding round at TikTok, basically a mini app build covering list rendering, form handling, API integration, and accessibility. More involved than I expected for a single session.

Build a list view that renders items from an in-memory array. CSS class names must use double underscores (BEM-style, like list__item). Single underscores will fail the tests.
Add a form to create new list items. On a failed submission (simulated 400 error), preserve the user's input and show a validation message. On success, append the new item and clear the form.
Fetch list data from a backend API and render it, handling loading, success, and error states. Make sure locally added items don't get duplicated when server data comes back.
Walk through your approach to accessibility (labels tied to inputs, correct button types), idempotent updates, predictable re-renders, event handling, state management, error handling, file/component structure, and how you'd test all of this.

“The double underscore thing is easy to miss if you're not already writing BEM.”

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TikTok·Data Scientist·Technical Phone Screen

Jul 2026

A TikTok data science interview built entirely around two open-ended fintech scenarios, no behavioral questions, just raw SQL and product thinking under pressure. The schema was fixed and you had to work within it, which made the FinCrime part especially tricky when you started second-guessing your proxy logic.

A new Ultra subscription plan just launched. Define what success looks like using a primary metric, diagnostic metrics, and guardrail metrics. Then describe the main validity risks and how you'd address them.
Write SQL using only the provided tables to compute the metrics you defined for the Ultra subscription launch evaluation.
Propose a rule-based approach to flag suspicious transactions for the financial crime team, then write SQL that outputs either suspicious user IDs with a risk score and triggered rules, or suspicious transaction IDs with flags.
Walk through the false-positive and false-negative tradeoffs in your FinCrime detection approach and explain how you would evaluate and iterate on the rules over time.

“This part felt manageable until they pushed on guardrail metrics.”

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