TikTok Interview Questions — Page 11

TikTok·Software Engineer·Technical Phone Screen

May 2026

TikTok software engineer interview with a graph traversal problem that had a lot of moving parts. The follow-up questions on edge cases and scaling pushed me harder than I expected.

Given a directed or undirected graph with n nodes and m edges where each node has an integer rating, find the top k distinct nodes reachable from a starting node s. Break ties by smaller node ID, avoid revisiting nodes, and return results in descending rating order. Analyze your time and space complexity and justify your data structure choices.
How does your solution change if k is close to the total number of reachable nodes?
What happens to your approach if node ratings can change while the traversal is still in progress?
How would you redesign the solution if the graph is too large to fit in memory?

“I went with BFS plus a min-heap of size k, which felt right.”

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TikTok·Product Manager·Onsite - Product Sense / Strategy

May 2026

TikTok PM interview with one product sense question about e-commerce. Pretty straightforward session, though walking through a full user journey on the spot is trickier than it sounds.

What is your favorite e-commerce platform and can you walk through the experience a user has from start to finish?

“I picked a platform I actually use, which helped, but I underestimated how much structure the user journey part needed.”

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TikTok·Data Scientist·Technical Phone Screen

May 2026

Technical screen for a Data Scientist role at TikTok, kicked off with the classic self-intro question. Nothing wild, but it set the tone for the rest of the conversation.

Walk me through your background, the projects you've worked on, and the impact you've had.

“I rambled a bit.”

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TikTok·Data Scientist·Technical Phone Screen

May 2026

TikTok data science interview focused on Trust & Safety, specifically around designing metrics for a content-moderation A/B test and evaluating a customer-service chatbot's knowledge base. Two meaty scenario-based questions in one session, which felt like a lot to cover.

In a content-moderation A/B test where harmful content is rare, what short-term user-facing metrics would you track to detect impact quickly, and why those specifically?
How would you design an experiment and choose evaluation metrics to assess the quality and usefulness of a customer-service chatbot's knowledge base?

“Low prevalence is the real wrinkle here.”

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TikTok·Data Scientist·Technical Phone Screen

May 2026

Python tech screen for a Data Scientist role at TikTok. Pretty focused, just one coding problem the whole time, which I wasn't expecting to be as tricky as it turned out to be.

Given a dictionary where each key maps to a list of numbers, write a Python function that returns a new dictionary where each value is the mean of the unique numbers from the original list.

“I jumped straight to set() for deduplication and it worked fine, but I second-guessed myself mid-explanation and started rambling about order preservation, which was completely irrelevant for computing a mean.”

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TikTok·Machine Learning Engineer·Onsite - Behavioral / Leadership

May 2026

TikTok ML engineer interview with a project deep-dive format. You pick two projects, one from an internship and one from research, and walk through the full arc of each. Pretty standard structure but the level of detail they expect is no joke.

Walk me through an internship project: what was the problem, what did you own, what technical decisions did you make and why, what challenges came up, what was the impact, and what would you change with more time?
Walk me through a research project using the same framework: problem definition, your ownership, key technical choices, challenges faced, measurable outcomes, and one thing you'd do differently.

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

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TikTok·Data Scientist·Technical Phone Screen

May 2026

TikTok data scientist interview that went deep into causal inference for ad measurement. One big technical question that covered a lot of ground, felt more like a take-home prompt read aloud than a conversational interview.

You can't randomize ad exposure because users differ on age, education, and income. Design a causal inference approach to estimate the average treatment effect of ad exposure on conversions, covering DAG construction, propensity score modeling, IPW and doubly robust estimators, diagnostics, sensitivity analysis for unobserved confounding, post-treatment bias avoidance, and variance estimation. Also discuss when diff-in-diff or CUPED would be preferable and what assumptions they require.

“This was basically a dissertation prompt compressed into one interview question.”

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TikTok·Software Engineer·Technical Phone Screen

May 2026

TikTok software engineering interview that leaned heavily into metrics design and experimentation. The question was basically a full product analytics case and it went deeper than I expected for an SWE role.

Pick a project and walk through how you'd define its primary outcome metrics, secondary metrics, and guardrails. Include precise definitions (what events count, what time windows, what denominators), your instrumentation and data quality plan, and how you'd design an experiment or observational study covering sampling, power, effect size, seasonality, and heterogeneity. Also discuss pitfalls like metric gaming, selection bias, and Simpson's paradox, and how you'd set up monitoring and alerting for regressions.

“This was a lot.”

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TikTok·Product Manager·Onsite - Product Sense / Strategy

May 2026

PM interview at TikTok with a customer experience scenario framed around Amazon. One question, product sense heavy, felt like a case study more than a standard interview.

You're a PM at Amazon and you've just been notified that customers are churning. How do you improve the customer journey and experience?

“The Amazon framing threw me a bit since I was interviewing at TikTok, so I spent a second wondering if there was a trick to it.”

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TikTok·Product Manager·Hiring Manager Screen

May 2026

Interviewed for a PM role at TikTok, mostly focused on my background straddling the US and China and whether I was actually committed to working out of Beijing. Pretty conversational but the relocation question had some real weight to it.

Based on your experience living and studying in both the US and China, what differences stand out to you, and how would you apply those observations when building products for a global audience?
What factors matter most to you when you're deciding which internship or project to take on?
What draws you to ByteDance and TikTok, and are you genuinely open to relocating to Beijing full-time?

“This was the question I felt most prepared for and also the one I probably over-explained.”

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