How difficult are LinkedIn interview questions?

LinkedIn interview difficulty varies by role and level but is generally medium-to-hard for technical roles. For software engineers expect algorithmic coding problems that are often LeetCode-medium-to-hard complexity, plus harder system design for senior levels. Data scientist and machine learning engineer rounds emphasize applied statistics, experiment design, model evaluation, and production ML system tradeoffs rather than purely theoretical proofs. Data engineer and analytics roles focus on scalable data pipelines, SQL performance, and practical ETL challenges. Interviewers expect clear thinking under time pressure, scalable designs, and strong communication; failing to justify tradeoffs or to explain assumptions is the most common failure mode.

What is the LinkedIn interview process and where do these 142 LinkedIn interview questions appear?

LinkedIn hires through a staged process starting with a recruiter screen, a technical phone screen or online assessment, then a virtual onsite loop of four to five interviews that combine coding, system or ML design, and behavioral rounds. The 142 questions in this set map across Data Scientist, Software Engineer, Machine Learning Engineer, and Data Engineer tracks: expect coding and data-structure problems in software engineering rounds, SQL and experiment/statistics problems in data science rounds, ML system and recommendation design for MLE roles, and pipeline and performance problems for data engineers. Senior candidates face heavier design and leadership evaluation.

How should I structure a preparation timeline to cover 142 LinkedIn interview questions before my onsite?

Plan a 6–10 week timeline depending on your starting level. Spend weeks 1–2 refreshing fundamentals: data structures, SQL, probability, and core ML concepts. Weeks 3–6 alternate focused practice blocks for each role represented in the 142 questions: two days of coding problems, one day of systems or modeling design, and one day of SQL/experimentation work per week. Reserve the final 1–2 weeks for timed mock interviews, behavioral STAR stories, and reviewing weak spots. Spread practice across real interview-like conditions with a shared editor for coding and a whiteboard or doc for designs.

What are the key subtopics I should prioritize across positions at LinkedIn?

Prioritize role-specific themes revealed by actual question titles: for data scientists focus on logistic regression and backprop intuition, causal experiment design, diagnosing traffic or feed relevance drops, imbalance handling, and variance reduction methods in ensembles. For software engineers prioritize efficient randomized data structures, O(1) insert/delete, top-K ranking services, common string and subarray algorithms, and debugging distributed queues. Machine learning engineers should emphasize recommender-system design, feature sampling and weighted-index sampling, K-means convergence, and practical ML pipeline monitoring. Data engineers should demonstrate robust stack implementations and measurable impact from pipeline projects.

Any standout tips and common pitfalls for LinkedIn interviews I should watch for?

Emphasize clear assumptions, measurable success metrics, and tradeoffs in every design or analysis answer. For data roles always tie model or experiment choices back to business metrics and experiment validity; avoid asserting causation without addressing confounders. For coding, prioritize correctness with clear complexity analysis and then optimize incrementally. In system and ML design, call out data pipelines, monitoring, alerting, and rollback strategies. Common pitfalls include vague requirements, skipping edge cases, ignoring scale and reliability, and weak communication; rehearse concise explanations and have two to three strong impact stories ready.

LinkedIn Interview Questions (Updated 2026) — Page 6

LinkedIn Interview Questions

Practice 142 real LinkedIn interview questions for 2026. Covers all top categories — Coding & Algorithms, System Design, Analytics & Experimentation, Data Manipulation (SQL/Python), and Behavioral & Leadership — across Software Engineer, Data Scientist, Machine Learning Engineer, and Data Engineer roles. Real questions from actual interviews with detailed solutions; this collection is designed for focused interview preparation that prioritizes coding and scale-first problem solving alongside rigorous metrics thinking. Expect LinkedIn interviews to evaluate production-ready tradeoffs, clear metricization of ranking and relevance, and the ability to diagnose live-traffic regressions. For Software Engineer candidates, recurring themes include constant-time randomized data structures and frequency-weighted sampling, Top-K ranking service design and distributed-scaling considerations, plus classic array/string and stack-with-max algorithmic problems. Data Scientists should be ready for model fundamentals and optimization (logistic regression, backprop, Adam), causal and experimentation diagnostics for feed/homepage drops, and sampling/variance concerns in ranking metrics. Machine Learning Engineers will see recommendation and skills-inference system design, clustering convergence and probabilistic sampling questions, and production alerting/spike-detection. Data Engineers encounter efficient data-structure implementations tied to measurable production impact.

Questions

142

Company

Updated

04.11.2026

142 Questions 1 Company04.11.2026

PLTCHK

"I got asked a hardcore MCM DP question and I saw it on PracHub as well. Solved that question in 5 minutes. Without PracHub I doubt I could solve it in 5 hours. Though somehow didn't get hired, perhaps I guess I solved it too fast? /s"

_The_TaNk_

"Believe me i'm a student here jn US. Recently interviewed for MSFT. They asked me exact question from PracHub. I saw it the night before and ignored it cause why waste time on random sites. I legit wanna go back and redo this whole thing if I had chance. Not saying will work for everyone but there is certainly some merit to that website. And i'm gonna use it in future prep from now on like lc tagged"

ChrisSenior SWE, LinkedIn

"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."

sleepy33

"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."

JakeSenior ML Engineer, Lyft

"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."

nuggetlord

"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."

CarlosFull Stack, Shopify

"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."

boba.tea.vibes

"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."

AndySWE-II, Google

"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."

couchpotato99

"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."

ShrutiData Engineer, Salesforce

"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."

midnightramen

"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."

BiancaFrontend Eng, Figma

"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."

tambrahm007

"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."

toa

"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."

PLTCHK

_The_TaNk_

ChrisSenior SWE, LinkedIn

"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."

sleepy33

"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."

JakeSenior ML Engineer, Lyft

"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."

nuggetlord

CarlosFull Stack, Shopify

"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."

boba.tea.vibes

"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."

AndySWE-II, Google

"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."

couchpotato99

"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."

ShrutiData Engineer, Salesforce

"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."

midnightramen

"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."

BiancaFrontend Eng, Figma

"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."

tambrahm007

"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."

toa

"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."

Showing 20 results

Role

LinkedIn Interview Questions

LinkedIn Interview Questions

Solve min window & animal conflicts

Explain variance reduction in random forests

Single Queue vs Multiple Queues — Service Design

Diagnose Job Application Decline: Funnel Analysis and Segmentation

Design O(1) insert/delete and frequency-weighted random

Explain HTTP verbs, CSS, and accessibility

Explain a project and handle ambiguity

Choose better bank queue and describe distributions

Implement alert queries and spike detection

[SQL] Job Ad Metrics with Applicant Filter

How would you lead a team to improve quality?

Reverse a linked list

Implement fast sampling for weighted k-sided die

Compute total covered interval length

Design Experiments for Email Campaign & Messaging Update

Measure Success of New B2B Product

Find dictionary words matching a phone digit string

Implement map and render to DOM

Differentiate Java final, finalize, finally

Design distributed parallel job processing

Frequently Asked Questions

Explore more LinkedIn interview questions

Featured LinkedIn interview prep guides