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Interview Questions
Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.
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Showing 4561–4590 of 9403 results
- LinkedInMediumData ScientistHow to analyze Simpson's paradox
This question evaluates competency in causal reasoning, statistical inference, experimental design, and detection of Simpson's paradox within the Analytics & Experimentation domain.
Analytics & ExperimentationTechnical Screen - LinkedInHardData ScientistHow to diagnose traffic and measure relevance?
This problem tests your ability to diagnose an unexplained drop in engagement metrics by decomposing a complex user funnel, isolating root causes using multidimensional data, and designing a robust validation framework.
Analytics & ExperimentationTechnical ScreenRoot Cause AnalysisMetrics StrategyFunnel Analysis - LinkedInEasyData ScientistHow would you lead a team to improve quality?
This question evaluates leadership and technical execution competencies for a data scientist in a tech lead role, including work planning, delegation, accountability, stakeholder communication, root-cause diagnosis of product quality issues, metric definition, and delivering projects with measurable impact.
Behavioral & LeadershipTechnical Screen - LinkedInMediumSoftware EngineerImplement Fast Power with Negative Exponents
This problem tests your ability to implement the exponentiation by squaring algorithm while correctly handling edge cases like negative exponents and integer overflow.
Coding & AlgorithmsOnsiteAlgorithmsMathBit Manipulation - LinkedInMediumMachine Learning EngineerImplement K-Means and Explain Convergence
This problem tests the implementation of the K-means clustering algorithm from scratch, requiring an understanding of the iterative refinement process, distance metrics, and the underlying mathematical objective.
Coding & AlgorithmsTechnical ScreenClusteringUnsupervised LearningAlgorithms - LinkedInHardMachine Learning EngineerImplement a Text-Embedding Recommender Training Pipeline
Tests the ability to structure an end-to-end, leakage-resistant training pipeline for a text-embedding recommender, covering profile flattening, embedding caching, temporal splits, binary classification, and artifact serialization.
Machine LearningTechnical Screenrecommender-systemsfeature-engineeringnlp-embeddings - LinkedInMediumData EngineerImplement a stack supporting max and popMax
This question evaluates understanding of data structures and algorithmic complexity, focusing on designing a stack variant that supports efficient retrieval and removal of the current maximum while preserving stack behavior.
Coding & AlgorithmsTechnical Screen - LinkedInMediumMachine Learning EngineerImplement alert queries and spike detection
This problem tests your ability to process a stream of events with time-based constraints, requiring an efficient sliding-window approach and the use of monotonic data structures for spike detection.
Coding & AlgorithmsOnsiteSliding WindowData StructuresStreaming - LinkedInMediumSoftware EngineerImplement an LRU cache with follow-ups
This question evaluates understanding of core data structures and algorithms for designing an efficient LRU cache as well as knowledge of concurrency and synchronization for thread-safe access.
Coding & AlgorithmsOnsite - LinkedInMediumData ScientistImplement fast sampling for weighted k-sided die
This question evaluates understanding of probabilistic algorithm design, numerical stability, and efficient data-structure implementation for constant-time sampling from categorical distributions.
Coding & AlgorithmsTechnical Screen - LinkedInMediumSoftware EngineerImplement map and render to DOM
This question evaluates a candidate's skills in vanilla JavaScript utility implementation and DOM rendering, covering array and plain-object iteration semantics, higher-order functions, input validation, error handling, and safe text rendering for browser environments.
Software Engineering FundamentalsHR Screen - LinkedInMediumData ScientistImplement stream random sampling in Python
This question evaluates understanding of streaming algorithms, uniform random sampling, and probabilistic guarantees for maintaining a fixed-size sample from an unbounded data stream (reservoir-sampling concepts).
Coding & AlgorithmsTechnical Screen - LinkedInMediumData ScientistImprove Profile Completion Rate
Evaluates analytics and experimentation strategy for improving LinkedIn profile completion. Strong answers define value-weighted completion metrics, segment gaps, prioritize interventions, and test impact with guardrails.
Analytics & ExperimentationOnsite - LinkedInMediumSoftware EngineerIntroduce yourself and discuss challenges
This question evaluates communication, leadership, self-awareness, and the ability to concisely articulate technical impact, trade-offs, and measurable outcomes.
Behavioral & LeadershipHR Screen - LinkedInMediumSoftware EngineerLargest Sum of a Non-Empty Contiguous Subarray
Given an integer array, return the largest sum of any non-empty contiguous subarray, including arrays in which every number is negative. This classic phone-screen problem tests efficient array processing and careful handling of edge cases such as all-negative input.
Coding & AlgorithmsOnsite - LinkedInMediumSoftware EngineerLexicographically Smallest Topological Order of a Dependency Graph
Given n labeled nodes and directed precedence edges, return an ordering that respects every edge, choosing the lexicographically smallest valid ordering, or an empty list when a cycle makes ordering impossible. It tests topological sorting, cycle detection and deterministic tie-breaking.
Coding & AlgorithmsOnsite - LinkedInMediumSoftware EngineerLongest Run of Ones After One Flip
This problem tests your ability to manage a sliding window with a flexible constraint, specifically counting zeros to determine the maximum length of a sequence after a single modification.
Coding & AlgorithmsTechnical ScreenSliding WindowTwo PointersArray - LinkedInMediumSoftware EngineerMaximum Product of a Contiguous Subarray With Negatives and Zeros
Given an integer array that may contain negative numbers and zeros, return the largest product of any non-empty contiguous subarray. The problem tests careful reasoning about sign changes, zeros and single-element subarrays under tight input-size limits.
Coding & AlgorithmsOnsite - LinkedInHardData ScientistMeasure Causal Impact of Self-Selected App Redesign
LinkedIn causal inference prompt on measuring a self-selected app redesign, covering potential outcomes, ATT, propensity matching or weighting, staggered difference-in-differences, event studies, covariates, balance, and pre-trend validation.
Statistics & MathOnsite - LinkedInHardData ScientistMeasure Relevant Feed Success
This question tests the ability to define North Star metrics for a social feed and design an experimentation framework that accounts for long-term ecosystem health and cross-side network effects.
Analytics & ExperimentationTechnical ScreenProduct AnalyticsA/B TestingMetrics - LinkedInMediumData ScientistMeasure Success of New B2B Product
Evaluates success measurement for a new LinkedIn B2B SaaS product at account and seat levels. Strong answers define activation, engagement, value, retention, expansion, anomaly analysis, and growth prioritization.
Analytics & ExperimentationOnsite - LinkedInEasySoftware EngineerMerge Two N-ary Trees by Matching Node Keys
Merge two rooted n-ary trees in which every node has an integer key, combining nodes only when their keys match under matching parents. Tests recursive tree traversal, matching children by key, handling roots with different keys, and producing a canonical preorder encoding of the merged tree.
Coding & AlgorithmsTechnical Screen - LinkedInHardSoftware EngineerMerge and Serialize N-ary Trees
Tests recursive tree manipulation, immutable merging semantics, and robust string serialization/deserialization with input validation.
Software Engineering FundamentalsTechnical Screentreerecursionparsing - LinkedInMediumSoftware EngineerMinimize adjacent-color assignment cost
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Minimize adjacent-color assignment cost states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - LinkedInEasySoftware EngineerMinimum index distance between two given words in a word list
Coding problem: given a list of words and two different target words that both appear in it, return the smallest distance between an index of one word and an index of the other. It tests single-pass scanning with position tracking, handling of repeated occurrences, and time complexity analysis.
Coding & AlgorithmsTechnical Screen - LinkedInMediumMachine Learning EngineerPlan and lead a large recommendation project
This Behavioral & Leadership question evaluates leadership, execution planning, cross-functional coordination, resourcing, and stakeholder communication skills in the context of machine learning recommendation product development.
Behavioral & LeadershipOnsite - LinkedInMediumData ScientistPresent Insights from Course Supply and Participation Data
Analyze course catalog supply and learner participation using time trends, category comparisons, utilization measures, and evidence-based presentation.
Analytics & ExperimentationOnsite - LinkedInMediumSoftware EngineerRandomized String Multiset With Average O(1) Insert, Remove and Weighted Random Pick
Design a collection of strings that allows duplicates and supports insert, remove and a random pick in average constant time, where each stored occurrence is equally likely to be returned. It tests hash map and array layout, index bookkeeping on removal, and how string keys change the cost analysis.
Software Engineering FundamentalsTechnical Screen - LinkedInHardSoftware EngineerReduce Stale Listings in a Job Marketplace
Design an auditable staleness-detection and remediation engine for a global job marketplace that aggregates heterogeneous signals, enforces graduated interventions, and supports low-latency employer appeals.
System DesignTechnical ScreenDistributed SystemsEvent-Driven ArchitectureAudit Logging - LinkedInMediumData ScientistResolve Conflicting A/B Test Results in Cities
Evaluates interpretation of conflicting A/B test results across cities using Simpson's paradox and stratified estimands. Strong answers check weighting, SRM, heterogeneity, confidence intervals, and rollout criteria.
Analytics & ExperimentationTechnical Screen
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