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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 4351–4380 of 4616 results
- UpstartEasyData ScientistEstimate impact without experiments and pick variant
This question evaluates causal inference and experimental-analysis competencies in Analytics & Experimentation and Data Science, covering observational estimands, causal identification assumptions and biases, uncertainty quantification for A/B/C tests, multiple-comparisons reasoning, and post-launch forecasting and monitoring.
Analytics & ExperimentationTechnical Screen - UpstartHardData ScientistEvaluate channels and allocate budget
This question evaluates competency in marketing analytics and experimentation for a Data Scientist role, covering funnel analysis, conversion and CAC metrics, attribution modeling, response-curve-based budget allocation, and incremental test design using channel-level spend and outcome data.
Analytics & ExperimentationTechnical Screen - UpstartHardData ScientistExplain Treatment Results and Recommend Launch Criteria for Experiments
Explain Treatment Results and Recommend Launch Criteria for Experiments evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationTechnical Screen - UpstartHardData ScientistExplain career moves and defend moat
This question evaluates a candidate's ability to narrate career progression with quantified outcomes, analyze and defend a company's sustainable competitive advantage (moat) using a strategic framework, and present high-visibility decisions and trade-offs under deadline, testing competencies in self-awareness, strategic reasoning, risk assessment, stakeholder communication, and metrics-driven impact reporting for a Data Scientist role in the Behavioral & Leadership category. It is commonly asked to assess how well a candidate synthesizes narrative and quantitative evidence for leadership and cross-functional contexts, and it targets both conceptual understanding of strategic frameworks and practical application of metrics and presentation trade-offs.
Behavioral & LeadershipTechnical Screen - UpstartHardData ScientistExplain tackling ambiguity and defending a decision
This question evaluates judgment under ambiguity, data-driven decision-making, stakeholder alignment, trade-off analysis, and post-decision learning in a data science context, and is categorized within Behavioral & Leadership interview topics.
Behavioral & LeadershipTechnical Screen - UpstartMediumSoftware EngineerFind max word letter span
This question evaluates proficiency in string processing, character mapping, and algorithmic analysis by requiring computation of per-word letter spans while accounting for case normalization, punctuation handling, ties, duplicates, and edge-case word forms.
Coding & AlgorithmsTechnical Screen - UpstartHardData ScientistHow to Architect a Personalized Ads Serving System
This interview question evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer for How to Architect a Personalized Ads Serving System states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Machine LearningTechnical Screen - UpstartMediumData ScientistHow would you measure causal impact?
Answer causal-impact and three-variant experiment prompts with clear estimands, quasi-experimental assumptions, validation, uncertainty, by-hand CTP intervals, multiple-comparison caveats, business guardrails, and Bayesian forecasting for production conversion.
Analytics & ExperimentationTechnical Screen - UpstartMediumData ScientistNavigate Conflicting Priorities in Cross-Functional Collaboration
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Navigate Conflicting Priorities in Cross-Functional Collaboration states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipTechnical Screen - UpstartMediumData ScientistSolve drunk-passenger probability and simulate outcome
This question evaluates probabilistic reasoning and stochastic-process intuition, including use of invariant arguments, closed-form derivations, statistical estimation via Monte Carlo simulation, and analysis of algorithmic time and space complexity.
Statistics & MathTechnical Screen - ValonMediumSoftware EngineerDesign an In-Memory Database
This question evaluates a candidate's skills in data modeling, in-memory data structures, index design, and query/filter semantics for a flexible schema-less record store.
Coding & AlgorithmsTechnical Screen - ValonHardSoftware EngineerImplement an In-Memory Query Engine
Design and implement an in-memory query engine capable of ingesting records and executing structured queries with comparison, membership, and logical operators.
Coding & AlgorithmsTechnical ScreenData StructuresDesignRecursion - ValonHardSoftware EngineerImplement an in-memory SQL-like table
This problem tests your ability to design a flexible, in-memory table structure that supports dynamic schema definition, data storage, and basic relational query operations.
Coding & AlgorithmsTechnical ScreenData StructuresAPI DesignAlgorithms - ValonMediumSoftware EngineerLoan Ledger: Fee-First Payments and Out-of-Order Event Processing
Implement loan accounting handlers in Python where fees increase the fee balance and payments pay down fees before principal, then build a ledger that accepts payment and fee events out of order. It tests keeping events ordered by accounting sequence, updating later balances without reprocessing the whole history, handling ties and overpayments, and analyzing per-call cost.
Software Engineering FundamentalsTechnical Screen - ValonMediumSoftware EngineerSubscription Ledger: Credits-First Charges With Backdated Events
Implement billing event handlers where credits pay down usage before the subscription fee, then build a ledger that accepts charge and credit events out of chronological order and recomputes only the balances that a backdated event actually invalidates.
Software Engineering FundamentalsTechnical Screendata-structuresdesignordering - VantaMediumSoftware EngineerDesign streaming test logger and queries
This question evaluates a candidate's ability to design streaming data structures and time-series algorithms to track state transitions and compute interval queries, covering competencies in online/event-processing algorithms, interval overlap aggregation, and algorithmic complexity analysis within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - VantaMediumSoftware EngineerDesign test-run logging and query functions
This question evaluates proficiency in time-series logging, event-driven state transitions, interval and sliding-window algorithms, and efficient data-structure design for streaming updates.
Coding & AlgorithmsTechnical Screen - VercelMediumSoftware EngineerCount Hits in the Past Five Minutes
Implement a five-minute hit counter with ordered timestamped operations, repeated hits, and an explicit 300-second expiration boundary.
Coding & AlgorithmsTechnical Screen - VerkadaMediumSoftware EngineerDesign Camera Health Monitoring
This question evaluates a candidate's competency in designing scalable, near-real-time monitoring systems, covering high-throughput heartbeat ingestion, compact per-device state management, detection of missing events, and handling duplicates, late arrivals, and ordering issues.
System DesignTechnical Screen - VerkadaMediumSoftware EngineerDesign a Camera Health Dashboard
This problem tests the ability to design a high-throughput ingestion system and a real-time state management strategy for time-sensitive IoT heartbeats.
System DesignTechnical ScreenIoTCachingScalability - VerkadaHardSoftware EngineerDesign camera access-control service
This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Design camera access-control service states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - VerkadaMediumSoftware EngineerDesign real-time per-status device counts
This question tests the ability to design a distributed system capable of aggregating real-time device heartbeat events into status counts while handling event-time latency and fault tolerance.
System DesignTechnical ScreenStream ProcessingDistributed SystemsScalability - VerkadaMediumSoftware EngineerDistribute a Large Matrix Transpose
Design a fault-tolerant, distributed system to transpose massive matrices that exceed single-machine memory using block tiling, idempotent worker execution, and completion tracking.
System DesignTechnical ScreenDistributed SystemsBatch ProcessingFault Tolerance - VerkadaHardSoftware EngineerFind and Merge Camera Alert Intervals
This question evaluates understanding of time-series processing, interval detection, and interval-merging algorithms, including handling thresholds, touching intervals, and open-ended alerts.
Coding & AlgorithmsTechnical Screen - VerkadaMediumSoftware EngineerFind motion intervals above threshold
This question evaluates understanding of time-series data processing and interval detection, focusing on grouping timestamped motion readings that exceed a numeric threshold and managing contiguous active segments.
Coding & AlgorithmsTechnical Screen - VerkadaMediumSoftware EngineerFind the Super Admin User Who Can Access Every Camera Through Nested Groups
Given permission triples linking users, groups and cameras, find the user who can access every camera through direct ownership or through nested, possibly cyclic group memberships. It tests modeling permissions as a directed graph, reachability that tolerates membership cycles, and edge cases such as an input with no cameras or a group that covers everything.
Coding & AlgorithmsTechnical Screen - VerkadaMediumSoftware EngineerFind users with access to all cameras
This question evaluates understanding of graph modeling and traversal techniques, particularly transitive closure, cycle detection, and BFS-based permission propagation across nested group relationships.
Coding & AlgorithmsTechnical Screen - VerkadaHardSoftware EngineerImplement WordGuess feedback scoring
This question evaluates proficiency in string processing, frequency counting, and edge-case handling by requiring implementation of Wordle-like feedback scoring for guess versus secret words.
Coding & AlgorithmsTechnical Screen - VerkadaMediumFrontend EngineerImplement a Camera List UI from a Defined Visual Contract
Implement a responsive React camera-card list with fixed preview ratios, status and missing-image states, semantic selection, and a clear visual-verification method.
Software Engineering FundamentalsTechnical Screen - VerkadaMediumSoftware EngineerImplement a JavaScript frame player controller
Implement a JavaScript frame player controller evaluates requirements, assumptions, structured reasoning, trade-offs, and verification in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Software Engineering FundamentalsTechnical Screen
Upstart
Vanta
Vercel
Verkada