Katkat

practice a little every day, paws crossed ♡

Quantitative Trader 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 1–8 of 8 results

  • Jane StreetMediumQuantitative Trader
    Analyze trading RFQ competitiveness data

    This question tests your ability to model order flow competitiveness by deriving features from trade logs and assessing the relationship between pricing aggressiveness and win probability.

    Machine LearningOnline AssessmentLogistic RegressionFeature EngineeringMarket Microstructure
  • Jane StreetEasyQuantitative Trader
    Bounds on the Probability of Rain on at Least One Weekend Day

    This question evaluates understanding of probability theory and dependence between events, specifically the ability to reason about bounds on the probability of a union given fixed marginals, which is a core competency for probabilistic modeling in Machine Learning and Data Scientist roles.

    Machine LearningTechnical Screen
  • Jane StreetMediumQuantitative Trader
    Dice Duel: 30-Sided Die vs. 20-Sided Die with One Blind Reroll

    This question evaluates probabilistic reasoning, expected-value comparison, and decision-making under uncertainty in discrete random processes. It is commonly asked to test a candidate's ability to reason about optimal stochastic decisions and trade-offs in blind reroll scenarios, classified under probability and decision theory within the Machine Learning domain and assessing conceptual understanding rather than practical implementation.

    Machine LearningOnsite
  • Jane StreetEasyQuantitative Trader
    Four Fair Coins: Expected Payoff and Pricing Two Magic Wands

    The question evaluates probabilistic reasoning, expected-value computation, and invariant-based state-space analysis as applied to adaptive operations on random variables and pricing contingent instruments.

    Machine LearningTechnical Screen
  • Jane StreetMediumQuantitative Trader
    Pricing a Mystery Money Box: Expected Value, Adverse Selection, and Competition

    This question evaluates probabilistic reasoning and economic-incentives competencies, including expected-value calculation, risk-neutral decision-making, adverse selection, and surplus division in bargaining contexts.

    Machine LearningTechnical Screen
  • Jane StreetMediumQuantitative Trader
    Sealed-Bid Auction for a Box of 200 Coin Flips (and an Informed Opponent)

    This question evaluates understanding of probability and expected-value reasoning, auction and game-theoretic strategic thinking, Bayesian inference under asymmetric information, and quantitative decision-making relevant to a Machine Learning-focused data scientist role.

    Machine LearningTechnical Screen
  • OptiverMediumQuantitative Trader
    Quant 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
  • SquarepointMediumQuantitative Trader
    Solve Probability and Statistics Questions

    This problem tests your understanding of OLS regression assumptions, the asymptotic behavior of sample estimators, and expected value optimization under probabilistic constraints.

    Machine LearningTechnical ScreenRegressionProbabilityStatistics