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Google interview notes, page 77 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·Data Scientist·Technical Phone Screen

May 2026
Google data scientist interview with a statistics-heavy question on truncated distributions. Nothing behavioral, just pure probability theory under mild pressure. The question had multiple parts so it felt like it kept going after I thought I was done.
  • If you only keep samples from a normal distribution where the value is greater than 1, what is the resulting distribution called, what is its formal PDF and CDF, and how would you generate random samples from it using at least two different methods?

“The name came to me quickly (truncated normal) but writing out the formal PDF tripped me up a bit.”

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Google·Product Manager·Onsite - Behavioral / Leadership

May 2026
Interviewed for a PM role at Google and got hit with a behavioral question about manager conflict. Pretty standard stuff but it still tripped me up a bit.
  • Tell me about a time you disagreed with your manager. How did you handle it?

“I had a story ready but it felt thin once I started telling it.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview question about handling a live experiment gone sideways. Pretty classic product sense setup but the specifics made it tricky to navigate cleanly.
  • You're the PM for Chrome and need to make a go/no-go call on auto-playing video ads. You're in a 5% rollout and just got word that negative feedback on Chrome pages with auto-play enabled is up 20%. What's your next move?

“I spent too long upfront trying to dissect what 'negative feedback' even means here, which was probably the right instinct but I got a bit lost in it.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Google SWE coding round, two related array problems back to back. The follow-up was the real interview, the first part was just warmup.
  • Given an integer array, find the longest strictly increasing contiguous subarray in a single pass with O(n) time complexity.
  • Now extend the previous problem: you're allowed to replace at most one element in the array with any value you want. What's the longest strictly increasing contiguous subarray you can achieve, and how do you compute it efficiently?

“Pretty standard once you see it.”

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Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Google SWE coding round, graph problem that looks simple on the surface but has a few ways to approach it. Nothing too wild but the union-find angle is easy to miss if you default straight to BFS.
  • Given an n x n adjacency matrix representing direct friendships, return the total number of friend circles (connected components), keeping in mind that friendship is transitive.

“My first instinct was BFS and it works fine, but I think they were nudging toward union-find.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Google SWE coding round with a graph shortest path problem. Pretty standard Dijkstra territory but the directed/weighted combo tripped me up a bit on edge cases.
  • Given a weighted directed graph, find the shortest path from a given source node to all other nodes. Return the total time to reach all nodes via shortest paths, or -1 if any node is unreachable.

“Went with Dijkstra pretty quickly, which was the right call, but I fumbled the unreachable node check at first.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
PM interview at Google with a product design question that crossed into hardware territory, which I was not expecting at all.
  • Design a physical product for Airbnb.

“I froze for a second because my whole prep was software-side.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview with a classic estimation question. Pretty standard product sense round but this one had enough moving parts to trip you up if you weren't careful about your assumptions.
  • How many drones would be needed to replace all FedEx package deliveries across the US?

“I started with total US packages per day, which I ballparked around 15 million across all carriers, then tried to figure out FedEx's rough share.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Google SWE interview with a machine learning theory question that felt deceptively simple on the surface.
  • Why does a deep neural network outperform a shallow one?

“I knew the general direction but fumbled the specifics.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Interviewed for a PM role at Google and got hit with a product improvement question about Pinterest. Pretty standard product sense round, nothing too wild.
  • How would you improve the Pinterest experience?

“I spent too long on the user segmentation piece and kind of rushed the actual improvement ideas at the end.”

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