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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 3091–3120 of 4616 results
- OptiverHardSoftware EngineerCalculate the Probability That Two Dice Sum to Seven
This question tests fundamental understanding of discrete probability, combinatorics, and the impact of conditional dependencies on outcomes.
Statistics & MathTechnical ScreenProbabilityCombinatoricsStatistics - OptiverHardSoftware EngineerCargo Order Allocation Across Departing Planes
This question evaluates competence in deterministic resource allocation, stateful simulation, and capacity-management under time constraints, exercising algorithmic reasoning and data-structure handling within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - OptiverMediumSoftware EngineerCompare common data structures and uses
Compare common data structures and uses evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - OptiverMediumSoftware EngineerCompute expectations, conditionals, odds, and distributions
This question evaluates proficiency in fundamental probability and statistics concepts — including expected value and variance, conditional probability, discrete arrival modeling, betting odds and the Kelly criterion, and combinatorics for draws without replacement — and is categorized under Statistics & Math.
Statistics & MathTechnical Screen - OptiverMediumData ScientistCompute expected coin flips to meet on octagon
Compute expected coin flips to meet on octagon evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Statistics & MathTechnical Screen - OptiverMediumSoftware EngineerCount nonnegative buy/sell sequences
This question evaluates combinatorial reasoning and algorithmic analysis by asking for the count of constrained buy/sell sequences, testing competence in counting under constraints and reasoning about sequence invariants.
Coding & AlgorithmsTechnical Screen - OptiverMediumSoftware EngineerDecide and implement DP/heap and approximation
This question evaluates dynamic programming for counting constrained subsequences, priority-heap implementation and API robustness for job scheduling, and heuristic approximation methods for NP-hard selection problems, along with algorithmic complexity analysis.
Coding & AlgorithmsTechnical Screen - OptiverMediumSoftware EngineerDemonstrate task switching and memory strategies
This question evaluates task-switching ability, working-memory management, interference control, and error-recovery strategies—core executive functions involved in rapid stimulus–response mappings.
Statistics & MathTechnical Screen - OptiverMediumSoftware EngineerDesign a circular queue data structure
This problem tests your ability to implement a fixed-capacity circular queue using a static array, focusing on efficient pointer arithmetic and state management.
Coding & AlgorithmsTechnical ScreenData StructuresArraysQueues - OptiverMediumSoftware EngineerDesign a queue and analyze tradeoffs
This question evaluates understanding of FIFO data structures, algorithmic complexity analysis, memory and cache behavior, and concurrent access concerns.
Coding & AlgorithmsTechnical Screen - OptiverHardSoftware EngineerDesign a subscription push service
Design a subscription push service 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 - OptiverMediumSoftware EngineerDesign an object-oriented queue and compare implementations
Design an object-oriented queue and compare implementations evaluates engineering fundamentals, trade-offs, examples, pitfalls, and operational implications 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 - OptiverHardSoftware EngineerDesign and backtest a trading strategy
This question evaluates a candidate's ability to design and rigorously evaluate a minute-level mean-reversion trading strategy, encompassing quantitative finance competencies such as signal construction, risk controls, position sizing, transaction-cost modeling, reproducible backtesting, and statistical validation; it belongs to the Analytics & Experimentation category within financial time-series and backtesting. It is commonly asked because it tests both practical implementation skills (reproducible backtests and walk-forward validation) and conceptual understanding (overfitting, data-snooping, and statistical significance testing), requiring a mix of practical application and conceptual statistical reasoning.
Analytics & ExperimentationTechnical Screen - OptiverMediumQuantitative ResearcherDesign dice betting strategy under time limit
This question evaluates probabilistic reasoning, expected-value computation, risk management and staking-strategy concepts including Kelly-style bet sizing, confidence-interval estimation, and return–variance trade-offs in the Statistics & Math domain.
Statistics & MathTechnical Screen - OptiverHardSoftware EngineerDetect Currency Arbitrage After a Cycle Fee
You are given a matrix of positive currency exchange rates, where rates[i][j] units of currency j are received for one unit of currency i. Work through the function contract, boundary cases, correctness argument, and time and space complexity expected in a production-quality solution.
Coding & AlgorithmsTechnical Screen - OptiverMediumSoftware EngineerDetect currency arbitrage with costs
This question evaluates a candidate's competency in algorithmic problem modeling, graph-based cycle detection, and numerical reasoning about exchange rates and transaction costs.
Coding & AlgorithmsTechnical Screen - OptiverMediumData ScientistExpected Wait for a Bus That Runs Late Half the Time
This question evaluates a candidate's understanding of probabilistic modeling and expectation calculations for stochastic arrival processes, touching on renewal-theory concepts and length-biased sampling phenomena relevant to timing and queuing problems.
Machine LearningTechnical Screen - OptiverEasyQuantitative ResearcherFermi Estimation with Confidence Intervals: How Many Houses Does One Year of US Netflix Spending Buy?
This question evaluates a candidate's quantitative estimation and uncertainty-quantification skills, focusing on decomposition into estimable factors, clear articulation of assumptions, calibrated confidence intervals, and updating estimates when new aggregate data are provided.
Machine LearningTechnical Screen - OptiverHardSoftware EngineerFind the Color Probability After Discarding Cards
This problem tests your understanding of conditional probability, combinatorics, and how dependent events (sampling without replacement) impact statistical expectations.
Statistics & MathTechnical ScreenProbabilityCombinatoricsStatistics - OptiverHardSoftware EngineerFind the Probability That the Three Smallest Dice Sum to Three
This problem tests combinatorics and probability theory by requiring the derivation of the exact probability that the three smallest values of four independent dice rolls sum to exactly three.
Statistics & MathTechnical ScreenProbabilityCombinatoricsStatistics - OptiverMediumQuantitative ResearcherIntroduce yourself and justify quant research fit
This question evaluates communication, motivation, collaboration, and quantitative engineering competencies, including domain skills such as low-latency systems, data/ML for signal generation, simulation/backtesting, probabilistic/statistical literacy, and rapid estimation under pressure.
Behavioral & LeadershipTechnical Screen - OptiverMediumSoftware EngineerMaintain Price Levels For A Single-Symbol Order Book
Design and implement a single-symbol limit order book that tracks individual orders and aggregates quantity by price level, supporting order additions, modifications, cancellations, and best price queries.
Coding & AlgorithmsTechnical Screenhash-tableheapdesign - OptiverMediumData ScientistMake Two Apple Piles Equal With Doubling Moves
This question evaluates algorithmic problem-solving and discrete-mathematics competencies, focusing on reasoning about state transitions, invariants, and number-theoretic constraints within the Coding & Algorithms domain for data scientist roles.
Coding & AlgorithmsTechnical Screen - OptiverHardData ScientistMarket-Making Estimation Game: Optimal Confidence-Interval Strategy Over 5 Rounds
This question evaluates probabilistic reasoning, decision-theoretic optimization of confidence intervals, and sequential risk–reward trade-offs by requiring interval estimation under a nonstandard scoring rule, relevant to a Data Scientist and categorized in Machine Learning/statistical decision theory.
Machine LearningTechnical Screen - OptiverHardQuantitative TraderOptimize interval-scoring strategy
This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Optimize interval-scoring strategy states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Statistics & MathTechnical Screen - OptiverMediumData ScientistProve a Tight Lower Bound on a Latin Square's Lower-Triangle Sum
This question evaluates combinatorial reasoning and discrete optimization skills—specifically understanding permutations in Latin squares, triangular-sum inequalities, and construction of extremal examples—within the Software Engineering Fundamentals domain for a Data Scientist position, and it primarily probes conceptual understanding with a constructive application component. Such problems are commonly asked to assess the ability to derive global bounds from local constraints and to exhibit matching constructions, signaling mathematical maturity and facility with combinatorial identities.
Software Engineering FundamentalsTechnical Screen - OptiverMediumQuantitative TraderQuant Trading Game: Expected-Value Betting and Market Making on Coins, Dice, and Cards
This question evaluates probabilistic reasoning, expected-value calculation, risk management, and market-making intuition under time pressure within a simulated trading game.
Machine LearningTechnical Screen - OptiverHardSoftware EngineerReviewing a Freight-Scheduler Codebase: Bugs, Data Structures, and Concurrency
This question evaluates a candidate's ability to perform code review and debugging on a large codebase, testing understanding of data structures, algorithmic complexity, deterministic allocation policies, capacity accounting, and concurrency correctness.
Software Engineering FundamentalsTechnical Screen - OptiverMediumSoftware EngineerSimulate return-weighted rebalancing strategy
Simulate return-weighted rebalancing strategy 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 - OptiverMediumSoftware EngineerSolve three mini-game algorithm tasks
Solve three mini-game algorithm tasks evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen
Optiver