Amazon Interview Questions
Practice 631 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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"Believe me i'm a student here jn US. Recently interviewed for MSFT. They asked me exact question from PracHub. I saw it the night before and ignored it cause why waste time on random sites. I legit wanna go back and redo this whole thing if I had chance. Not saying will work for everyone but there is certainly some merit to that website. And i'm gonna use it in future prep from now on like lc tagged"
"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."
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"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
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"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."
"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."
"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."
"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."
"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."
"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."
"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."
Explain work-simulation approach under ambiguity
Behavioral: Prioritizing and Delivering Under Ambiguity in a Time-Boxed Simulation Context You are a software engineer in a technical screen. You are ...
Describe a complex problem you solved
Behavioral questions 1. Complex problem: Tell me about a time you worked on a complex technical problem. - What made it complex (scale, ambiguity, ...
Compute and interpret quantile loss vs RMSE
Quantile (Pinball) Loss vs RMSE/MAE; Computations and Calibration You are evaluating probabilistic forecasts for a time series/ML regression task. You...
Design a robust traffic forecasting pipeline
Forecasting Daily Amazon Retail Traffic: End-to-End Design You are given 5 years of daily Amazon retail site traffic counts. Design an end-to-end fore...
Analyze an A/B test over last 7 days
A/B Test Readout and Decision (2025-08-26 to 2025-09-01) Context A 50/50 A/B experiment on the checkout flow ran for 7 days, from 2025-08-26 through 2...
Compute array modes with ties and no-mode rule
Write a function that returns the mode(s) of an integer array. Requirements: if all values are unique, return an empty list (there is no mode); allow ...
Choose regularization norms and model formulations
Regularization and model choice. 1) For linear and logistic regression, write the objective functions with L0, L1, L2, and L-infinity penalties in bot...
Design end-to-end regression for energy demand
End-to-End Daily Energy Prediction for Commercial Buildings Context You are asked to design and justify an end-to-end regression system that predicts ...
Design an end-to-end spam detection system
Design an End-to-End Email Spam Detection System You are asked to design a production-grade email spam detection system that meets the following const...
Quantify improvement and compute required sample size
A/B Test on Spam Rate: Sample Size, Inference, and Practical Pitfalls Context: You are evaluating a new classifier that aims to reduce the spam rate (...
Measure PMF for Alexa Shopping
Define and Measure Product–Market Fit (PMF) for Alexa Shopping Context You are designing a measurement plan to assess PMF for Alexa Shopping, where cu...
Demonstrate ownership and communication under pressure
Behavioral Interview: Ownership, Dive Deep, Raise the Bar (Data Scientist) Provide concise, data-backed stories using STAR (Situation, Task, Action, R...
Compute peak parking lot occupancy intervals
You are given logs from a parking lot system. Each log entry has the form: [carId, time, eventType] - carId is an integer identifying a car. - time is...
Demonstrate Leadership in Challenging Situations and Decision-Making
Demonstrate Leadership in Challenging Situations and Decision-Making Amazon Data Scientist Onsite — Bar-Raiser Behavioral Loop Context You will be ask...
Navigate Crises and Sustain Team Morale Under Pressure
Navigate Crises and Sustain Team Morale Under Pressure Behavioral & Leadership — Data Scientist Onsite Scenario You are working as a Data Scientist on...
Design A/B Test for New Amazon Recommendation Module
Design A/B Test for New Amazon Recommendation Module A/B Test Design: Home Page Recommendation Module Scenario Amazon plans to introduce a new product...
Explain Decision-Tree Training and Clustering Algorithms
Explain Decision-Tree Training and Clustering Algorithms Decision Trees and Clustering: Training Mechanics and Core Principles Context Technical/phone...
Identify P-Value Limitations and Complementary Approaches
Identify P-Value Limitations and Complementary Approaches A/B Testing: Limits of P-values and Better Decision Practices Scenario Your team is running ...
Design object model for an elevator system
Design the object-oriented model for an elevator (lift) system in a multi-floor building that may have multiple elevators. The system should support: ...
Design a scalable image-based social network
Design the backend system for a social networking website primarily focused on sharing images (similar in spirit to an image-centric social app). User...