Amazon Coding & Algorithms Interview Questions
Practice 695 real Amazon interview questions for 2026. Covers all top categories — Coding & Algorithms, Behavioral & Leadership, Machine Learning, Data Manipulation (SQL/Python), and System Design — across Software Engineer, Data Scientist, Machine Learning Engineer, Product Manager, and Business Intelligence Engineer roles. Real Amazon interview questions from actual interviews with detailed solutions; use this collection for interview preparation that emphasizes shipping at scale, measurable impact, and the company’s Leadership Principles. Expect coding-heavy assessments for Software Engineer candidates: frequent tree and dynamic-programming problems, two-array optimization patterns, nested object/path lookups, and system-design prompts that mirror product flows (online Minesweeper, pizza-ordering, credit-card and shipping/cost systems), plus leadership and collaboration behavioral prompts. Data Scientist rounds concentrate on experimentation and metrics (A/B design, hand p-values, D7 retention SQL), RAG/recommender evaluation, and product-impact analyses. ML Engineer questions focus on production model design, LLM/agent concepts, reliability (cold start, training stability, online vs offline gaps), and large-scale detection pipelines. PM interviews stress customer-obsessed stories, ambiguity, Alexa product launches, and domain-specific data pipelines. Prepare with timed coding practice, end-to-end experiment writeups, STAR stories framed to Leadership Principles, and mock system-design sessions.
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Prioritize Under a Tight Deadline
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Answer core behavioral questions for data roles
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Design an Online Minesweeper Platform
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Explain inheritance, polymorphism, constructors, destructors
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Build the Largest Available Sequence
This question evaluates algorithmic problem-solving skills in state simulation, constrained selection, and lexicographic sequence maximization, measur...
Build an end-to-end ML pipeline
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Implement ad matching and delivery routing
Implement ad matching and delivery routing Part A: Implement a data structure for an ad-matching service that supports add(campaign), remove(campaign)...
Assess Candidate's Alignment with Amazon Leadership Principles
Behavioral Interview: Amazon Leadership Principles for Data Scientists You are interviewing for a Data Scientist role where customer impact, ownership...
Implement Batch Gradient Descent for Linear Regression
Batch Gradient Descent for Linear Regression You are building a linear regression model from scratch and will optimize the parameters using batch grad...
Merge overlapping and adjacent ranges
Given an unsorted list of integer ranges represented as half-open intervals [start, end) with start < end, merge all overlapping or directly adjacent ...
Explain XGBoost Parallelism Strategies
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