LinkedIn interview notes, page 31 of 32

Large Enterprises

Most of these LinkedIn write-ups come from Software Engineers (156), then Product Managers (66) and Data Scientists (37). The most reported rounds are the technical phone screen (169), the product sense round (62), the system design round (42) and the behavioral / leadership round (20).

316 interview notes · updated Oct 2026

LinkedIn·Software Engineer·Technical Phone Screen

Jul 2026

LinkedIn data engineer interview with a coding question that was more of a data structures design problem than anything SQL or pipeline related. Not what I expected going in.

Design a MaxStack data structure that supports push, pop, top, peekMax, and popMax operations, where popMax removes the maximum element closest to the top if duplicates exist. All operations should run better than linear time.

“The push/pop/top part was fine, that's just a stack.”

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LinkedIn·Data Scientist·Onsite - Product Sense / Strategy

Jul 2026

Product data science interview at LinkedIn with two meaty product sense questions. Nothing behavioral, just pure case work. The kind of interview where you either have a framework in your head or you're winging it.

LinkedIn sees a material drop in weekly traffic from the Home Page to the Profile Page. How would you investigate whether this is a product bug, a logging issue, a user behavior shift, or an intentional improvement?
Design an experiment and success measurement framework for changing LinkedIn's Home Feed default from showing all content to showing only the most relevant content per viewer.

“The inline profile preview context is what makes this question interesting rather than generic.”

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LinkedIn·Data Scientist·Technical Phone Screen

Jul 2026

LinkedIn data scientist interview that went deep into probability theory, specifically around coin flip stopping times. Not your typical SQL or metrics question, this one felt more like a grad school exam than a product interview.

For a fair coin, what is the expected number of flips until you see two consecutive heads? Derive it using a state-based or Markov chain argument.
Now generalize: if the coin has probability p of heads, what is the expected number of flips to see HH?
For the fair coin case, derive the variance of T, the number of flips until HH appears. Walk through your full reasoning.

“I set up three states: start, one head seen, done.”

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LinkedIn·Software Engineer·Onsite - System Design / Architecture

Jul 2026

LinkedIn system design round for a software engineering role. The whole session was basically one giant distributed systems question that kept branching into sub-topics. Felt like I was defending a thesis by the end of it.

Design a distributed job execution system that runs many independent jobs in parallel across a cluster. Walk through the job model, APIs, how you partition work, scheduler and worker design, coordination, fault tolerance, idempotency, result aggregation, scaling, and consistency trade-offs.

“This question is basically five questions stapled together.”

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LinkedIn·Software Engineer·Onsite - Behavioral / Leadership

Jul 2026

Behavioral round at LinkedIn for a software engineer role. Four questions, all pretty standard but the coworker one tripped me up more than I expected.

What project are you most proud of, and why?
Tell me about a time you had to work with a difficult coworker.
Can you give an example of critical feedback you received and how you responded to it?
How do you make decisions quickly when you don't have enough information?

“I had an answer ready but rambled way too long on the technical details and forgot to tie it back to impact.”

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LinkedIn·Software Engineer·Technical Phone Screen

Jul 2026

LinkedIn software engineer interview with a classic tree problem and a follow-up that actually made me think harder than the main question.

Given a binary tree, find the lowest common ancestor of two given nodes. Follow-up: how does your approach change if every node has a pointer to its parent?

“The base recursive solution came back to me pretty quickly.”

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LinkedIn·Software Engineer·Onsite - Behavioral / Leadership

Jul 2026

Behavioral round at LinkedIn for a software engineer role. Two questions, both pretty standard for senior-level loops but they still made me think harder than expected.

Tell me about a time you proposed a technical initiative and had to get your manager and other stakeholders on board. How did you build the case, push back on objections, and eventually get alignment?
How do you avoid becoming a single point of failure on your team? What concrete things do you actually do around documentation, knowledge sharing, and distributing ownership?

“This one I actually felt okay about.”

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LinkedIn·Data Scientist·Technical Phone Screen

Jul 2026

LinkedIn DS interview with a SQL-heavy technical screen. Two parts to the same problem, nothing too exotic, but the histogram piece tripped me up more than I expected.

Given a table of article view events and a table mapping articles to their types, write SQL to find the number of distinct article types each user viewed on a specific date (2019-01-01).
Using the same tables but across all dates, build a histogram showing how many users viewed exactly N distinct article types. Return each possible value of N and the count of users at that value.

“Pretty straightforward join and group-by.”

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LinkedIn·Software Engineer·Technical Phone Screen

Jul 2026

LinkedIn SWE interview with a vehicle trip tracking problem. The question was cleaner than it looked at first but the edge cases are where they really want to see how you think.

Given a log of vehicle events (each with a license plate and an event type of ENTRY, ROAD, or EXIT), implement a function that counts the total number of completed trips across all vehicles, where a valid trip is exactly ENTRY followed by ROAD followed by EXIT in order.

“My first instinct was to just count sequences naively and I almost missed that the same plate can have multiple trips.”

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LinkedIn·Machine Learning Engineer·Technical Phone Screen

Jul 2026

LinkedIn MLE interview with a probability/geometry question that sounds straightforward but has a real gotcha buried in it. Not a coding marathon, more of a math reasoning session.

How would you sample a point (x, y) uniformly at random from the area of a circle with radius R centered at the origin? Why does picking the radius uniformly from [0, R] fail, and what's the correct approach?

“I knew something was off with the naive approach but couldn't articulate it cleanly at first.”

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