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.
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Implement a stack supporting max and popMax
Design a data structure that behaves like a stack but also supports retrieving and removing the current maximum value. Implement a class MaxStack with...
Do US members upload more videos than non-US?
You suspect video posting adoption differs between US and international members. Tables members - memberid INT (PK) - country VARCHAR (e.g., 'usa', '...
The Celebrity Problem
The Celebrity Problem At a party there are n people, labeled 0 to n - 1. Among them there may be exactly one celebrity — a person who satisfies both o...
How would you lead a team to improve quality?
Behavioral / Leadership — Leading a Team to Improve Quality You are acting as a Tech Lead (TL) for a small cross-functional team (e.g., 4–8 engineers ...
Design a meeting scheduler API
This question evaluates object-oriented design, interval data-structure and algorithmic thinking, and concurrent programming competence by requiring a...
Implement alert queries and spike detection
This question evaluates a candidate's skills in streaming data structures, time-windowed aggregation, in-memory analytics for high-throughput alert in...
Group words that map to same phone digits
Problem On a classic phone keypad (T9), letters map to digits: - 2: ABC, 3: DEF, 4: GHI, 5: JKL, - 6: MNO, 7: PQRS, 8: TUV, 9: WXYZ Given a list of lo...
How do you sample uniformly from an infinite stream?
This question evaluates understanding of streaming algorithms, randomized sampling and probability, and algorithmic space–time trade-offs involved in ...
Design a scalable key-value store
System Design: Distributed Key-Value Store Design a distributed key-value (KV) storage service for a large-scale backend system. The service should ex...
Design a Top-K search words service
Scenario Design a service that tracks user search queries and returns the Top-K most searched words/queries. Requirements Functional - API to record a...
Design a company-wide monitoring system
You are asked to design a monitoring system used company-wide. Goals - Collect and query telemetry for many services/hosts - Support alerting and dash...
Resolve Simpson’s paradox in email A/B test
This question evaluates understanding of Simpson's paradox, causal inference, experimental design, metric selection, and statistical inference within ...
Implement stream random sampling in Python
You are given an unbounded stream of items that cannot be stored entirely in memory. Write Python code to maintain a uniform random sample from the st...
Handle imbalance, validate samples, and avoid overfitting
This question evaluates competencies in handling class imbalance, choosing and interpreting evaluation metrics and decision thresholds, validating sam...
Design scalable job scheduler and query dashboard
Design a scalable, fault-tolerant job scheduling system. The system should allow clients to schedule background jobs (for example, sending emails or r...
Test whether US uploads more videos
This question evaluates a data scientist's competency in observational analytics, metric definition, confounder identification and control, and statis...
Analyze homepage drop and feed ranking
You are interviewing for a product data science role at LinkedIn. Answer the following two product-sense questions. 1. Diagnose a drop in Home Page ->...
Describe a project and its impact
You are interviewing for a Staff Data Engineer role supporting information security (e.g., detection engineering, alerting, network/security infrastru...
Design a system for LinkedIn Skills
Design an ML system for “LinkedIn Skills”. The system should infer and/or recommend skills for members, and support downstream use cases like search/r...
Design a metrics platform without alerting
This question evaluates a candidate's ability to design a scalable time-series metrics platform, covering data modeling for counters/gauges/histograms...