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Meta interview notes, page 163 of 238

FAANG / Big Tech

Most of these Meta write-ups come from Software Engineers (1,194), then Data Scientists (489) and Product Managers (453). The most reported rounds are the technical phone screen (1,190), the product sense round (466), the system design round (255) and the behavioral / leadership round (205).

2377 interview notes · updated Jul 2026

Meta·Data Scientist·Technical Phone Screen

Jun 2026
Meta data scientist interview focused on a product strategy case for Instagram. The whole thing was one big scenario about group chat and video features, which sounds straightforward until you realize they want you to weave together SQL, surveys, competitive research, and cost tradeoffs in a single coherent argument.
  • How would you build a data-backed case to convince leadership that Instagram should launch a group chat and group video-call feature?
  • How would you use the existing video_calls table to support the case for a group feature?
  • What additional qualitative or quantitative resources would you use to strengthen the business case?
  • What survey questions would you ask, and who would you target with those surveys?
  • Should there be a maximum group size for this feature, and how would you figure out what that cap should be?

“This is basically a mini product strategy pitch disguised as a data question.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta SWE interview, tree problem with a tricky space constraint. Not the hardest question on paper but the O(1) space requirement is where it gets interesting.
  • Given a binary tree where each node has a `next` pointer initialized to NULL, populate every node's `next` to point to the next node at the same level (or leave NULL if none exists). You must do this in O(1) extra space by leveraging the `next` chain you've already built on the parent level to traverse and wire up the children.

“The basic idea clicked pretty fast, BFS-style level linking.”

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Meta·Data Scientist·Technical Phone Screen

Jun 2026
SQL screen for a Data Scientist role at Meta. Two parts, both around reply engagement on a posts table. Pretty standard stuff but the zero-reply edge case tripped me up more than I'd like to admit.
  • Given a posts table and a replies table, return every post along with its reply count. Posts with zero replies should still appear in the result, showing a count of 0. Order by reply count descending, then post_id ascending.
  • Using the same schema, return only the post IDs of posts that have received no replies at all, ordered by post_id ascending.

“My first instinct was a regular join and I almost wrote it that way before catching myself.”

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Meta·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Meta SWE coding round, one question the whole time: minimum window substring. Classic sliding window problem but I kept second-guessing my pointer logic under pressure.
  • Given two strings s and t, find the shortest contiguous substring of s that contains all characters of t (with duplicates counted). Return an empty string if no such substring exists.

“I knew it was a sliding window problem pretty fast, two pointers, frequency map, shrink from the left when you have a valid window.”

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Meta·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Meta SWE coding round with an AI-enabled twist. The problem was a classic backtracking question but they apparently let you use AI tooling, which honestly changes the dynamic because you still need to explain your logic clearly.
  • Given an array of strings, find the maximum length of a concatenated string formed by selecting a subsequence such that all characters in the result are unique.

“Knew this one from practice but the bitmask part took me a minute to articulate out loud.”

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Meta·Software Engineer·Technical Phone Screen

Jun 2026
Meta SWE coding round, one algorithm question on finding the majority element in an array. Pretty standard stuff but worth knowing the Boyer-Moore voting approach cold before you walk in.
  • Given an array of integers, find the element that appears more than half the time (the majority element). Assume the array is non-empty and a majority element always exists.

“My first instinct was a hashmap to count frequencies, which works fine and I got it out cleanly.”

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Meta·Data Scientist·Technical Phone Screen

Jun 2026
Meta data scientist interview focused on notification systems, specifically how to measure whether push notifications help or hurt users and how to think through launching a new one. Pretty product-analytics-heavy, less coding than I expected.
  • How would you use data and metrics to determine whether an existing push notification is helpful or harmful to users, and what would your approach be to deciding whether to launch a new notification that tells users when a friend plans to attend an event?

“I started with funnel metrics which felt right, open rates, click-through, downstream engagement, but I fumbled a bit when they pushed on the 'harmful' side.”

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Meta·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Meta system design round, one big question that branched into two distinct sub-problems. The scope was wide enough that I kept second-guessing whether to go deeper on one part or keep moving.
  • Design a service where users can post short status updates and search through them, including full-text search over historical posts and geolocation-based search for nearby results.

“Two questions in one, basically.”

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Meta·Data Scientist·Technical Phone Screen

Jun 2026
Stats-heavy technical screen for a DS role at Meta. The whole thing centered on one fairly deep probability and statistics problem broken into three parts, so if you're not solid on CLT and sampling distributions you'll feel it.
  • Given a right-skewed sample of daily user comment counts, compute the mean, median, and 95th percentile, place them on a number line, and explain why mean > median > mode typically holds for right-skewed count data. Also explain why the median and p95 can be whole numbers.
  • If the true population has mean 3.0 and standard deviation 4.0 comments per user, and you sample 50 users, what is the approximate distribution of the sample mean by the central limit theorem? Give its mean, standard error, and 95th percentile, and compare that p95 to the individual-level p95 from the previous part.
  • If the sample size grows from 50 to 400 users, recompute the standard error and describe how the mean, median, and p95 of the sampling distribution shift relative to each other as n increases.

“The sample they gave was [0,0,0,1,1,1,2,2,3,3,3,4,4,5,6,7,10,15,20,40].”

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Meta·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Meta PM interview, product design question for a pretty niche user group. Short on details but the question itself is a solid one to prep for.
  • Design a product for roofers.

“I blanked for a second because I'd never thought about roofers as a user segment before.”

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