LinkedIn Interview Questions
Practice 147 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.
"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"
"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"
"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."
"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."
"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."
"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."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."
"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."
"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."
"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."
"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."
"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."
"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."
"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."
Handle imbalance, sampling, and overfitting
Machine Learning Fundamentals: Imbalance, Sampling, Overfitting, and Regularization You are asked several machine learning fundamentals questions in a...
Design a short-video recommender system
This question evaluates a data scientist's competency in end-to-end machine learning system design for recommender systems, including retrieval and ra...
Introduce yourself and discuss challenges
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Design a scalable calendar system
System Design: Multi-Tenant Calendar at Massive Scale You are designing a multi-tenant calendar platform used by hundreds of millions of users across ...
Train with imbalanced sampled data
You are training a binary classifier on a very large dataset where the positive class is rare. Because the full dataset is too large to train on direc...
Compare queueing systems and common distributions
LinkedIn Data Scientist Statistics Fundamentals You are asked a series of statistics fundamentals questions in a data science technical screen. Constr...
Merge two N-ary trees by key rules
You are given two N-ary trees A and B. Each node has: - key (string): unique among siblings (i.e., within a node’s children list, no two children shar...
How to diagnose traffic and measure relevance?
This question evaluates a data scientist's skills in traffic diagnostics, instrumentation validation, user-path and navigation analysis, causal reason...
Explain a project and handle ambiguity
Behavioral & Leadership: End-to-End Project + Ambiguous Production Incident You are interviewing for a Software Engineer (Onsite) role. Provide a conc...
Process Mutable Matrix Sum Queries
You are given a 2D integer matrix and a list of queries. There are two query types: - set r c v: update the value at row r and column c to v - get r1 ...
Design O(1) Randomized Multiset
This question evaluates data-structure design skills, understanding of hashing and randomization for uniform sampling, handling of duplicate elements,...
Measure Causal Impact of Self-Selected App Redesign
Measure Causal Impact of a Self-Selected App Redesign A mobile app ships a redesigned UI as a new version. Users opt in by upgrading, so a standard ra...
Design Experiments for Email Campaign & Messaging Update
Experiment Design for Concurrent Email Campaign and Messaging Feature Marketing will run an email campaign at the same time Product ships a new in-pro...
Resolve Conflicting A/B Test Results in Cities
A/B Test Paradox Across Two Cities You ran an A/B test in two geographies, City X and City Y. Within each city, variant A outperforms variant B. Howev...
Diagnose Job Application Decline: Funnel Analysis and Segmentation
Diagnose a Sharp Decline in Job Applications LinkedIn sees a sudden, sharp decline in its Job Application metric, defined broadly as completed job app...
Compute point-to-segment minimum distance
This question evaluates understanding of computational geometry and numerical robustness, testing the ability to compute Euclidean distances between a...
Design an exception monitoring system with top‑K
This question evaluates the ability to design a scalable, low-latency exception monitoring system focusing on streaming ingestion, event grouping/fing...
Design distributed parallel job processing
Design a Distributed System for Parallel Job Execution Context You are asked to design a highly available, horizontally scalable service that executes...
Analyze Profile Traffic Drop
This question evaluates a data scientist's competency in product-metrics analysis, instrumentation validation, segmentation and attribution, and causa...
Count Article Types Viewed
Count Article Types Viewed You are given article view events and article metadata. Table 1: article_views — one row per article view event. | Column |...