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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Explain Multi-Armed Bandit Principles
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Describe using customer data
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Design an A/B Test for Dashboard Engagement Impact
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Quantify improvement and compute required sample size
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Evaluate concession gift-card policy with DID
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Compare Random Forests vs Gradient Boosting rigorously
Technical ML Choice: Random Forest vs. Gradient-Boosted Trees for Large-Scale Binary Classification Problem Setup You need to choose between a Random ...
Process real-time enter/exit events and actives
You receive a real-time stream of events with schema: user_id (str), channel (str), event_type ("enter"|"exit"), ts (UTC ISO timestamp). A user can ‘e...
Explain weight initialization methods and goals
This question evaluates a candidate's understanding of weight initialization in deep neural networks, assessing competencies in training dynamics such...
Describe overfitting and L1/L2 regularization
Define overfitting in machine learning and explain why it is harmful. Then describe L1 and L2 regularization: - How each one modifies the loss functio...
Explain the bias–variance trade-off
Explain the bias–variance trade-off in supervised learning. In your answer, cover: - What bias and variance mean in the context of a prediction model....
Solve three coding tasks: binary search, tree path, subarray
Solve three coding tasks: binary search, tree path, subarray Solve the following coding tasks: 1) In a sorted array, every value appears exactly twice...
Evaluate RAG System Accuracy and Cost Control Strategies
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Prioritize Under a Tight Deadline
Tell me about a project where you had to deliver under a tight deadline. In your answer, be prepared to explain: - What the project was and why the de...