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.
"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."
Design a scalable metrics monitoring system
Design a Metrics Monitoring System for Large-Scale Services Context You are designing a metrics monitoring system for large-scale, cloud-native micros...
Compare queueing systems and common distributions
Question You are asked a series of statistics fundamentals questions in a data science technical screen. 1. Queueing. A bank with 5 tellers can be org...
Handle imbalance, sampling, and overfitting
You are asked several machine learning fundamentals questions: 1. You are building a binary classifier with a highly imbalanced target. How would you ...
Find k closest values in a BST
Given a binary search tree with n nodes and a real target t, return k node values whose distances to t are smallest. Implement an algorithm with O(log...
Minimize adjacent-color assignment cost
You are given H linear items (e.g., houses) and an H×C cost matrix where cost[i][c] is the cost of assigning color c to item i. Adjacent items cannot ...
Describe leading an infrastructure initiative
Behavioral: End-to-End Infrastructure Initiative You are asked to describe a time you led an end-to-end infrastructure initiative. Address the followi...
Count Article Types Viewed
Question You are given article view events and article metadata. Table 1: article_views — one row per article view event. | Column | Type | Descriptio...
Determine sanitized palindrome in string
Write a function that determines whether a string is a palindrome after removing non-alphanumeric characters and ignoring case (e.g., punctuation, whi...
Introduce yourself and discuss challenges
Behavioral Interview Prompt: 5‑Minute Self‑Introduction + Challenge (STAR) Context You are interviewing for a Software Engineer role and have an HR sc...
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 ...
Design a distributed key-value store
Design a Distributed Key–Value Store (Technical Screen) Context You're designing a cloud-native, multi-tenant key–value (KV) storage service for inter...
Evaluate an email test with confounding
A marketing team wants to evaluate a new email campaign. They tested Email A and Email B across two cities (San Francisco and New York) over two weeks...
Explain a past project and critique a prior team
Interview prompts 1. Project deep dive: Pick a past project you worked on and walk through it end-to-end. Be ready to use a whiteboard to explain arch...
Implement fast sampling for weighted k-sided die
You must sample from a categorical distribution over k outcomes with probabilities p1..pk (sum to 1) without using built-in categorical samplers. You ...
How do you lead and drive impact?
You are interviewing for a senior or tech-lead data scientist role. Prepare to answer the following behavioral prompts with concrete examples from you...
Implement K-Means and Explain Convergence
Implement the K-means clustering algorithm for a set of points in Euclidean space. Your implementation should: - Take as input a dataset of points and...
Frequent Traveler Case
Frequent Traveler: Definition, Features, Modeling, and Product Use Context: You are a data scientist at a professional networking platform. Using user...
One of the most comprehensive LinkedIn DS Product Cases!
LinkedIn Profile Completion: Measurement, Diagnosis, and Improvement Context: You are a Data Scientist working on LinkedIn's Profile experience. "Prof...
Design a max-stack with efficient operations
Design a stack that supports push (x), pop(), top(), peekMax(), and popMax(). The popMax operation must remove and return the maximum element; if ther...
Describe challenging teamwork and feedback handling
Behavioral Interview Prompts (Software Engineer, Onsite) Context: You are a software engineer interviewing onsite. Prepare concise answers (1–2 minute...