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Google interview notes, page 129 of 215

FAANG / Big Tech

Most of these Google write-ups come from Software Engineers (1,167), then Product Managers (686) and Data Scientists (125). The most reported rounds are the product sense round (667), the technical phone screen (660), the behavioral / leadership round (252) and the onsite coding round (214).

2146 interview notes · updated Oct 2026

Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview with a classic ambiguous scenario question. One round, product sense focus, nothing too wild but it requires you to actually have a framework in your head before you walk in.
  • It's your first day as a PM at Google. Users are reporting that the internet feels slow. Walk through how you'd handle it.

“I spent way too long trying to define 'slow' before I even touched the problem structure.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE interview centered entirely on a trie-based autocomplete design problem. It went deeper than I expected, covering data structure choices, complexity analysis, and a full dry-run trace through several operations.
  • Design and implement an autocomplete service using a prefix tree. Support insert(word, weight), update(word, newWeight), delete(word), and topK(prefix, k) returning the k highest-weight words under that prefix, with lexicographic tiebreaking. Walk through the data structures you'd store at each node to make topK efficient, analyze time and space complexity per operation, and discuss trade-offs between caching sorted results at nodes versus computing on demand.

“This was the whole interview basically.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview with a system design question focused on disaster resilience. One question, pretty open-ended, and I spent way too long on the wrong part of it.
  • How would you design an ATM system that continues to function during a natural disaster?

“I jumped straight into offline mode and cached transaction logs, which felt smart at the time, but I kind of forgot to anchor on the user first.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE coding round, one question, tree traversal with a twist. Pretty standard for a technical phone screen but the space constraint tripped me up a bit.
  • Given the root of a binary tree, return node values in zigzag level order (left to right for the first level, right to left for the next, alternating). Return a list of lists. Target O(n) time and O(w) space where w is the max tree width.

“I got the BFS part pretty quickly but fumbled on the direction-flipping logic.”

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Google·Software Engineer·Online Assessment (OA)

Jun 2026
Google SWE coding round with a string/prefix filtering problem. Pretty standard stuff but the sorted output requirement is easy to forget under pressure.
  • Given a list of words and a prefix string, return all words that start with that prefix, sorted in lexicographical order. Return an empty list if none match.

“My first instinct was to just filter and sort, which works fine.”

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Google·Data Scientist·Onsite - Coding / Algorithms

Jun 2026
Coding round at Google for a Data Scientist role. Two algorithm questions, nothing too exotic, but the second one had a follow-up about index recovery that I wasn't fully prepared for.
  • You have access to a function that returns a uniform random sample between 0 and 1. Write a function that returns a 2D point uniformly distributed over the square with corners at (-1, -1) and (1, 1). You can call the provided function as many times as you need.
  • Given an integer array, find the length of the longest strictly increasing contiguous subarray. Also discuss time and space complexity, and explain how you would recover the actual start and end indices of that subarray.

“This one was pretty approachable once I realized you just scale and shift each coordinate independently.”

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Google·Machine Learning Engineer·Onsite - Coding / Algorithms

Jun 2026
Google MLE coding round, one algorithmic problem the whole session. The problem looked deceptively clean but the implementation details had a few gotchas that tripped people up, myself included for a bit.
  • Given an integer array, find the sum of element-sums across all contiguous subarrays where every adjacent pair differs by exactly +1 or exactly -1 (strictly monotone step sequences). Singleton subarrays count. Solution must run in O(N) time.

“I spent the first few minutes trying to enumerate subarrays and immediately knew that was going nowhere fast.”

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Google·Data Scientist·Technical Phone Screen

Jun 2026
Causal inference question for a DS role at Google, focused on a real product scenario involving Workspace Chat. Pretty technical and open-ended, the kind where you can go in a dozen directions and it's not obvious which one they want.
  • The product team wants to know if a new chat notification design is actually driving more daily active users in Google Workspace Chat. How would you design a study to estimate its causal impact on engagement, and walk through your identification strategy, the data you'd need, your assumptions, and how you'd validate them?

“This one sprawls fast.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview with a single product design question about redesigning a cane. Pretty open-ended, which I wasn't expecting for a hardware-adjacent prompt.
  • How would you design a new cane?

“I fumbled the opening because I jumped straight into features without clarifying who the user actually is.”

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Google·Data Scientist·Technical Phone Screen

Jun 2026
Google data scientist interview, looked like a written technical screen covering a pretty wide range of stats and ML topics all at once. Four distinct problems in one sitting, from hand-computing a Welch t-test to choosing regularization methods for correlated predictors. Dense stuff.
  • Hand-compute a two-sided p-value using Welch's t-test for two samples (n1=20, mean1=5.2, sd1=1.1 vs n2=24, mean2=4.6, sd2=1.5). Walk through the t-statistic, Satterthwaite degrees of freedom, and the resulting p-value to three decimal places. Also explain why Welch's is the right call over a pooled t-test here.
  • For a Poisson process with rate λ=2 events per hour: first, find P[N(1.5) ≥ 3]. Second, given that exactly one event occurred in the first two hours, what is the probability that event happened within the first 0.5 hours? Name the property you're using.
  • You have 200 standardized predictors with block correlations around 0.9 and n=500. Choose between LASSO, Ridge, and Elastic Net for a task that requires both prediction accuracy and some interpretability. Explain the trade-offs, how you'd tune λ and α using nested cross-validation, and what the high within-group correlations do to selection stability and prediction error.
  • You have 25 paired observations per subject, the two measurements have unequal variances, and the data shows mild non-normality. Which test do you use: paired t-test, Welch's t-test, or a nonparametric alternative? Justify your assumption choices and state what effect size you'd report.

“The arithmetic is genuinely annoying to do by hand.”

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