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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 1711–1740 of 9403 results
- Boston Consulting GroupMediumData ScientistQuery top spenders and 7-day growth
This question evaluates proficiency in SQL data manipulation, including aggregations, date-range filtering, joins, window functions for ranking and tie-breaking, and computing revenue shares and growth rates within a relational schema.
Data Manipulation (SQL/Python)Technical Screen - Boston Consulting GroupHardData ScientistReduce overfitting under constraints
This question evaluates a candidate's competency in machine learning for mitigating overfitting in tabular regression under production latency constraints, testing knowledge of regularization, model complexity control, feature engineering, validation strategies, and experimental design.
Machine LearningTechnical Screen - Boston Consulting GroupEasyData ScientistScale and Normalize: When to Use Each Method?
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 Scale and Normalize: When to Use Each Method? states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Machine LearningOnline Assessment - Boston Consulting GroupMediumData ScientistSummarize impact and lessons from your resume
This question evaluates a data scientist's ability to communicate measurable impact, design and track metrics, manage stakeholders and conflicts, and demonstrate accountability through concrete project examples, testing Behavioral & Leadership competencies specific to the Data Scientist role.
Behavioral & LeadershipTechnical Screen - Boston Consulting GroupEasyData ScientistTrain GradientBoostingClassifier with 5-Fold Cross-Validation
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 Train GradientBoostingClassifier with 5-Fold Cross-Validation states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Machine LearningOnline Assessment - Boston Consulting GroupMediumData ScientistTransform messy transactions with pandas
This question evaluates proficiency in large-scale data manipulation and feature engineering using pandas, covering timestamp normalization across time zones, deduplication and last-write-wins semantics, data validation, memory-efficient aggregation, rolling-window statistics, and top-k categorical extraction for merchant categories.
Data Manipulation (SQL/Python)Technical Screen - Boston Consulting GroupMediumData ScientistVisualize and Clean SKU Sales Data for Outliers
This question evaluates data manipulation and exploratory data analysis skills, including aggregation, outlier detection (IQR/Z-score) and visualization using Python libraries such as pandas and matplotlib/seaborn.
Data Manipulation (SQL/Python)Technical Screen - BoxMediumSoftware EngineerCompute Top-K word frequencies under a path
Compute Top-K word frequencies under a path 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 & AlgorithmsOnsite - BoxMediumSoftware EngineerDesign out-of-order windowed stream processor
Design out-of-order windowed stream processor 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 & AlgorithmsOnsite - BoxMediumSoftware EngineerDiagnose failures via SSH and large logs
Diagnose failures via SSH and large logs 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 DesignOnsite - BoxHardSoftware EngineerExplain and diagram your past system architecture
Explain and diagram your past system architecture 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 DesignOnsite - BoxMediumSoftware EngineerFlip a specific bit in an integer
This question evaluates a candidate's understanding of bitwise operations and low-level integer manipulation, along with the ability to reason about the time and space complexity of bit-level operations.
Coding & AlgorithmsOnsite - BoxMediumSoftware EngineerIdentify and fix deadlock in locked code
Identify and fix deadlock in locked code 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 DesignOnsite - BoxEasySoftware EngineerImplement a Leaky Bucket Rate Limiter
This question evaluates understanding of rate-limiting algorithms, time-based state management, and concurrent programming concepts, including synchronization and test design for boundary and timing behaviors.
Coding & AlgorithmsOnsite - BoxHardSoftware EngineerImplement a leaky-bucket rate limiter
Implement a leaky-bucket rate limiter 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.
Coding & AlgorithmsOnsite - BoxMediumSoftware EngineerSolve classic troubleshooting & algorithm tasks
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Solve classic troubleshooting & algorithm tasks states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsOnsite - BrexMediumSoftware EngineerAnswer Behavioral Questions
This question evaluates a candidate's behavioral competencies such as ownership, communication under pressure, conflict resolution, accountability, and motivation reflected in long-term goals.
Behavioral & LeadershipTechnical Screen - BrexMediumSoftware EngineerBuild AI-Assisted Full-Stack Transactions App
This question evaluates full‑stack engineering competencies including API design, data persistence, input validation, transactional integrity for monetary data, frontend-backend integration, automated testing, and developer documentation.
System DesignTechnical Screen - BrexMediumSoftware EngineerBuild a React color multi-select dropdown UI
This question evaluates front-end React skills including component architecture, state management, data-driven rendering, accessibility considerations, and performance trade-offs involved in implementing a multi-select dropdown that presents selected colors' properties.
Software Engineering FundamentalsTechnical Screen - BrexMediumSoftware EngineerBuild a Simplified Venmo-Style Peer-to-Peer Payments App with AI Tools
An AI-assisted coding round prompt: build a simplified Venmo-style peer-to-peer payments app with users, balances, payments and transaction history, using any AI coding tool. It tests scoping a vague prompt, exact money handling, atomic and idempotent payments under concurrency, and the ability to review and explain generated code.
Software Engineering FundamentalsOnsite - BrexMediumSoftware EngineerDebug and Explain Fixes
This question evaluates a candidate's debugging and root-cause analysis skills, familiarity with unit testing and regression prevention, and ability to modify a small codebase to fix defects within the coding and algorithms domain.
Coding & AlgorithmsTechnical Screen - BrexHardSoftware EngineerDesign Points-from-Transactions Service
This question evaluates system design and distributed-systems competency, focusing on transaction processing, idempotency and deduplication, monetary precision and rounding, consistency models, data modeling, and operational controls like observability and fraud prevention.
System DesignTechnical Screen - BrexMediumSoftware EngineerDesign a Peer-to-Peer Money Transfer System
Design a peer-to-peer money transfer product with accurate balances and history despite retries, crashes, and concurrent spending. Define APIs, transfer states, durable accounting, atomic movement, recovery, reconciliation, authorization, and the boundary between an in-memory prototype and production.
System DesignOnsite - BrexEasySoftware EngineerImplement discounted card purchases
This question evaluates implementation-level skills in resource accounting and state management, specifically handling gem-cost mappings, per-color discounts, bounded arithmetic, and transactional updates to player state.
Coding & AlgorithmsTechnical Screen - BrexMediumSoftware EngineerSplendor-Style Card Purchases with Gem Costs, Color Discounts and Concurrent Buys
Model a Splendor-style card game in code: check whether a player's five-color gem inventory can afford a card, make an all-or-nothing purchase, and apply discounts earned from cards already owned. A follow-up asks how to keep one player's simultaneous purchase requests safe and consistent.
Software Engineering FundamentalsTechnical Screen - BridgeMediumSoftware EngineerDesign Minesweeper and Optimize Click Performance
This question evaluates a candidate's competence in data structures, graph traversal and flood-fill concepts, complexity analysis, and scalable system design for sparse board representations.
Coding & AlgorithmsTechnical Screen - BridgeMediumSoftware EngineerDesign signup and login service
This question evaluates understanding of authentication system design, secure password storage practices, API endpoint and request/response modeling, database schema design, and session or token-based login state management.
System DesignTechnical Screen - BridgeMediumSoftware EngineerImplement a Stepped Iterator
Design and implement a stepped iterator class that wraps an underlying iterator or sequence, advancing by a configurable step size on each call. This tests iterator design, state management, invariant preservation, and edge-case handling.
Software Engineering FundamentalsTechnical ScreenDesignIteratorsData Structures - BridgeMediumSoftware EngineerSelect an Object by a Dynamic Integer Field
Implement a clean, defensive utility function to select a dictionary from a collection based on the minimum or maximum value of a dynamic integer field, properly handling missing keys and ties.
Software Engineering FundamentalsTechnical Screendata-manipulationpythonclean-code - BridgeMediumSoftware EngineerSolve path normalization and nested iterator
This question evaluates proficiency in string/path normalization, manipulation of hierarchical data structures, stack-based iterator design, lazy versus eager flattening strategies, and algorithmic time/space complexity analysis in the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen
Boston Consulting Group
Box
Brex