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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.
- 9403
- Questions
- 546
- Companies
- 11
- Topics
- 8
- Languages
Showing 3151–3180 of 4616 results
- OtherMediumData ScientistCompute and estimate Markov transition probabilities
This question evaluates understanding of discrete-time Markov chains, multi-step transition probabilities and empirical estimation of transition matrices, testing probabilistic reasoning and matrix-based computation in the Statistics & Math domain for a Data Scientist role; it is commonly asked because it probes both theoretical grasp of stochastic processes and practical data-driven parameter estimation. At an applied algorithmic abstraction level, it requires explicit mapping of state labels to matrix indices, computing k-step transitions from a given row-stochastic matrix, estimating transition probabilities from observed one-step transitions, and addressing zero-outgoing-observation cases and any chosen smoothing policy (or justification for none).
Statistics & MathTechnical Screen - OtherEasyData ScientistCompute multi-step Markov probabilities and estimate transitions
This question evaluates understanding of discrete-time Markov chains, computation of multi-step transition probabilities from a one-step transition matrix, and empirical estimation of transition matrices from observed state-pair data including handling states with zero outgoing transitions.
Statistics & MathTechnical Screen - OtherMediumAnalytics EngineerContinue Entry Numbers for a Daily Incremental Batch
Continue per-context entry numbering for a daily batch using stored maximums, ordered row numbers, and correct new-context handling.
Data Manipulation (SQL/Python)Technical Screen - OtherHardData ScientistDecide launch with asymmetric costs
This question evaluates a data scientist's ability to integrate statistical inference (p‑values, Type I/II errors, and prior probabilities) with decision analysis and financial impact assessment (NPV, rollout and rollback costs) in the context of A/B testing.
Analytics & ExperimentationTechnical Screen - OtherHardData ScientistDecide launch with p=0.10 at alpha 0.05
This question evaluates a data scientist's competency in statistical inference and experiment decision-making, including frequentist hypothesis testing, conditional power and sample-size planning, Bayesian updating, and cost-sensitive risk analysis.
Statistics & MathTechnical Screen - OtherMediumData ScientistDefend fit and handle pressure in finance interview
This Behavioral & Leadership interview question evaluates a candidate's ability to translate data science experience into FP&A and finance analytics competencies—quantifying prior impact, handling monthly close and variance analysis, revenue forecasting and headcount/opex tracking, leveraging SQL/Excel, and managing stakeholder pressure.
Behavioral & LeadershipTechnical Screen - OtherHardData ScientistDefine goals and success metrics for subscriber-only features
This question evaluates a data scientist's competency in product analytics and experimentation, specifically goal selection, success metric definition, ROI calculation, cannibalization analysis, and end-to-end experiment and instrumentation design for subscriber-only features.
Analytics & ExperimentationTechnical Screen - OtherMediumData ScientistDesign anomaly detection and handle imbalanced logistic regression
Design a fraud detection setup for 50M transactions at a 0.4% fraud rate: a supervised logistic regression model plus an unsupervised anomaly detector for new merchants with no labels. Cover time-based splits, delayed labels, imbalance, calibration, and a cost-based threshold where a missed fraud costs far more than a false alarm.
Machine LearningTechnical Screen - OtherHardData ScientistDesign metrics and experiment
This question evaluates a candidate's competency in experimental design, success-metric definition, event instrumentation, causal inference for heterogeneous treatment effects, and statistical power and sample-size calculations for subscription-product analytics.
Analytics & ExperimentationTechnical Screen - OtherMediumData ScientistDesign metrics resilient to data quality
This question evaluates the ability to design robust data-quality metrics and apply SQL window-function techniques for deduplication and time-windowed completeness calculations, focusing on quantifying how ingestion delays, duplicates, and negative amounts can bias payment metrics.
Analytics & ExperimentationTechnical Screen - OtherMediumData ScientistHandle unprofessional, prescriptive interviewers
This question evaluates interpersonal communication, conflict management, stakeholder negotiation, time management, and the ability to succinctly surface technical and data-quality risks during a constrained SQL screening, reflecting competencies relevant for data scientists in collaborative settings.
Behavioral & LeadershipTechnical Screen - OtherEasyData ScientistHow would you measure and experiment on harmful content?
This question evaluates a data scientist's competency in measuring and experimenting on harmful user-generated content, focusing on severity quantification, metric selection, and randomized experiment design within the analytics and experimentation domain.
Analytics & ExperimentationTechnical Screen - OtherHardSoftware EngineerImplement a multi-button click detector
This question evaluates competency in real-time event stream processing, per-button state management, and timing-based classification of input events such as distinguishing single versus long presses.
Coding & AlgorithmsTechnical Screen - OtherMediumData ScientistImplement multiplication without using the multiplication operator
This question evaluates proficiency in bitwise arithmetic, integer overflow semantics, sign handling, and algorithmic efficiency for implementing multiplication without using multiplication or division operators.
Coding & AlgorithmsTechnical Screen - OtherMediumAnalytics EngineerMaintain Entry Numbers with Incremental Loads and Historical Backfills
Design incremental per-context entry numbering with idempotent state, contiguous-gap backfills, and correct handling of interleaved late events.
System DesignTechnical Screen - OtherMediumAnalytics EngineerNumber Entries Within Each Conversation
Assign one-based entry numbers per conversation using timestamp and identifier ordering in a PostgreSQL window-function query.
Data Manipulation (SQL/Python)Technical Screen - OtherMediumQuantitative ResearcherOptimal Stopping with a Ten-Sided Die and a Reset
Derive optimal stopping thresholds for a fair ten-sided accumulation game, then account for the continuation value of a one-time zero reset.
Statistics & MathTechnical Screen - OtherMediumData ScientistSolve window-function SQL without joins
This question evaluates proficiency with SQL window functions, including running and cumulative sums, LAG/forward-fill event logic, ranking functions (RANK/DENSE_RANK/ROW_NUMBER), tie-breaking strategies, and temporal date arithmetic for payments and subscription events.
Data Manipulation (SQL/Python)Technical Screen - Otter.AiMediumData EngineerDefend a Data Pipeline Architecture and Its Trade-offs
Prepare to defend a production data pipeline you genuinely built or changed. The prompt tests how you connect requirements to architecture, compare alternatives, explain replay and backfills, diagnose a hard failure, quantify outcomes, and reflect on ownership and trade-offs.
System DesignTechnical Screen - Otter.AiMediumSoftware EngineerEvaluate Arithmetic Expressions
This problem tests your ability to parse and evaluate a string representing a mathematical expression with basic operator precedence, typically requiring a stack-based approach or a recursive descent parser.
Coding & AlgorithmsTechnical ScreenStackString ParsingMath - Otter.AiEasySoftware EngineerExtend a Key-Value Store with Commits and Explicit Rollover Semantics
Design a versioned key-value store supporting staging, atomic commits, point-in-time snapshot reads, and automated rollover compaction.
System DesignTechnical ScreenKey-Value StoreMVCCConcurrency - Otter.AiMediumData EngineerFind Every Project with the Most Employees
Build a PostgreSQL aggregation that returns every project tied for the largest employee count. This compact exercise checks grouping, maximum selection, tie preservation, empty-input behavior, and careful use of primary-key guarantees.
Data Manipulation (SQL/Python)Technical Screen - Otter.AiMediumData EngineerFind the Highest-Paid Employee in Each Department
Work through a tie-aware PostgreSQL problem that finds every highest-paid employee in each department. It assesses relational reasoning, correct joins, duplicate-name handling, and precise output semantics without assuming a single winner.
Data Manipulation (SQL/Python)Technical Screen - Otter.AiMediumSoftware EngineerFixed-Width Text Display
This question tests a candidate's ability to implement greedy line-packing and space-distribution algorithms, core string manipulation skills evaluated in software engineering interviews. It assesses practical application of text layout logic, including handling edge cases like single-word lines and justified formatting with uneven space distribution.
Coding & AlgorithmsTechnical Screen - Otter.AiMediumSoftware EngineerImplement an Arithmetic Expression Evaluator
This problem tests your ability to parse and evaluate mathematical expressions containing non-negative integers, addition, subtraction, multiplication, and nested parentheses using a stack-based approach or recursion.
Coding & AlgorithmsTechnical ScreenStackParsingMath - Otter.AiMediumSoftware EngineerIn-Memory Key-Value Store with Nested Transactions
This problem tests the ability to implement a nested transactional key-value store using stack-based state management and scope shadowing.
Coding & AlgorithmsTechnical ScreenHash MapStackTransactions - Otter.AiEasySoftware EngineerValidate Password Against Multiple Rules
This problem tests your ability to efficiently iterate through a string while maintaining multiple state-based flags to satisfy diverse validation criteria.
Coding & AlgorithmsTechnical ScreenStringsValidationAlgorithms - PDT PartnersMediumMachine Learning EngineerList All Positive Divisors of an Integer in Ascending Order, Then Beat Square-Root Time
Given a positive integer up to one trillion, return every positive divisor in ascending order, each listed once. The task tests divisor enumeration, correct handling of perfect squares and 64-bit values, and a follow-up asking whether the running time can grow more slowly than the square root of n.
Coding & AlgorithmsTechnical Screen - PDT PartnersMediumMachine Learning EngineerProject Deep Dive: Low-Latency LSTM Inference at Scale and the LSTM vs Transformer Choice
A project deep dive on a small LSTM model served for large-scale, latency-sensitive inference. The candidate must explain the deployment hardware, latency requirement and use case, how inference latency was reduced, why an LSTM was chosen over a Transformer, and whether that choice still holds today.
Machine LearningTechnical Screen - PalantirHardSoftware EngineerDesign a scalable interview question bank
Design a scalable interview question bank evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen
Otter.Ai
Palantir