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Data Scientist 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 1–12 of 12 results

AdiaEasyData Scientist
Calculate Playback Counts per Stream
This question tests the ability to perform relational database joins and use aggregate functions (COUNT) with grouping to summarize event-level data.
Software Engineering FundamentalsTechnical ScreenSQLJoinsAggregation
BnpEasyData Scientist
Explain and compute option delta
Evaluates understanding of option delta, the differing intuitions/signs for calls versus puts, and the ability to compute deltas under the Black–Scholes model; commonly asked to assess quantitative reasoning about derivative sensitivities, model-based pricing, and hedging concepts.
Software Engineering FundamentalsTechnical Screen
BnpEasyData Scientist
Find expected tosses to see a coin pattern
Assesses probabilistic reasoning and stochastic-process modeling skills, focusing on expected stopping times for pattern occurrences in repeated independent trials and related concepts like state-space representation and overlap effects.
Software Engineering FundamentalsTechnical Screen
BnpEasyData Scientist
How do you split coins to match heads?
This question evaluates logical reasoning about invariants and combinatorial parity, testing the candidate's ability to design deterministic strategies under partial information; it falls under Software Engineering Fundamentals with relevance to probability and discrete mathematics for a Data Scientist role.
Software Engineering FundamentalsTechnical Screen
Capital OneMediumData Scientist
Test and Run a Reproducible Data Science Pipeline
Design and implement a robust, testable Python data pipeline class that validates input data schemas, handles feature transformation, logs execution metrics, and produces versioned outputs. Write targeted unit and integration tests ensuring graceful failure on corrupted inputs.
Software Engineering FundamentalsTechnical ScreenPythonData PipelinesTesting
ImcEasyData Scientist
Find valid range of q for outcome probabilities
This question tests the ability to solve a system of linear inequalities derived from probability constraints, requiring an understanding of basic arbitrage-free pricing principles.
Software Engineering FundamentalsTechnical ScreenProbabilityInequalitiesFinance
J.P. MorganEasyData Scientist
Compute expected value of simple gambling games
This problem tests your understanding of expected value, probability distributions, and the mechanics of independent trials in simple gambling games.
Software Engineering FundamentalsTechnical ScreenProbabilityStatisticsExpected Value
MillenniumMediumData Scientist
Evaluate an Agentic Decision System End to End
This problem tests the ability to design an automated evaluation framework for an agentic system that transitions from rule-based to LLM-driven decision-making, focusing on decoupling metrics and ensuring safety.
Software Engineering FundamentalsTechnical ScreenLLM-OpsEvaluationSystems-Design
Morgan StanleyMediumData Scientist
Estimate Greeks and hedging PnL
This question evaluates understanding of option Greeks (delta, gamma, vega), mental approximation of Gaussian probabilities, and the ability to reason about delta-hedged profit-and-loss under Black-Scholes model misspecification, categorized under Software Engineering Fundamentals for a Data Scientist role.
Software Engineering FundamentalsTechnical Screen
Morgan StanleyEasyData Scientist
Explain forward contracts and options
This question evaluates understanding of financial derivatives—specifically forwards and options—assessing competency in financial instruments, contractual rights and obligations, pricing concepts, and how these concepts inform data-driven modeling for a Data Scientist role.
Software Engineering FundamentalsTechnical Screen
OptiverMediumData Scientist
Prove 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
Wells FargoHardData Scientist
Organizing Code and Repositories: Functions, Classes, Comments, GitHub Files
A software practice question asks how you organize code into functions, classes and files, how and when you write comments, and which files a GitHub repository should and should not contain. It tests modular design judgment, documentation habits, and reproducible, secure project hygiene.
Software Engineering FundamentalsTechnical Screen