Amazon Data Scientist Interview Questions
Amazon Data Scientist interview questions are famously comprehensive because Amazon evaluates both technical depth and Amazonian fit. Expect a mix of SQL and Python problems, statistics and experiment-design questions, machine‑learning discussion, and behavioral probes tied to Amazon’s Leadership Principles. Interviews typically include an initial recruiter screen, one or two technical phone screens, and a loop of 4–6 on‑site/virtual interviews where each 45–60 minute slot focuses on a different competency. Interviewers look for clear problem decomposition, metric-driven thinking, defensible trade‑offs, and the ability to translate analysis into business impact. For effective interview preparation, build a structured plan: craft concise STAR stories mapped to Leadership Principles with quantified outcomes, drill SQL (joins, window functions, CTEs, performance), refresh statistics and A/B testing fundamentals, and sharpen Python/data-manipulation skills. Practice explaining assumptions, communicating results for technical and non‑technical audiences, and walking through model choices and evaluation metrics. Mock interviews and timed problem sets that simulate the loop rhythm are especially valuable to convert knowledge into polished, confident answers.
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"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."
"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."
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"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."
"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."
Compute an A/B test p-value by hand
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Generate Synthetic Clickstream Data with Python Function
Scenario The analytics team needs to generate synthetic click-stream records to test a new reporting pipeline before real traffic arrives. Question Wr...
Compute and interpret quantile loss vs RMSE
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Design idempotent daily loads with deduping
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Build a package-allocation model for couriers
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Process real-time enter/exit events and actives
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Analyze omitted-variable bias in regression
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Implement list overlap and dense-ranked word frequencies
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Walk through an A/B test end-to-end
Walk through how you would design, run, and analyze an A/B test for a product change. Your answer should include: - Hypothesis framing and choosing pr...
Answer core probability and inference questions
You are interviewing for a Data Scientist role. Explain/derive the following statistics fundamentals. 1. State the Central Limit Theorem (CLT). What c...
Select Top Customers Using Transaction Data Filters
transactions +----+---------+------------+--------+ | id | user_id | order_date | amount | +----+---------+------------+--------+ | 1 | 101 | 202...
Explain Decision-Tree Training and Clustering Algorithms
Decision Trees and Clustering: Training Mechanics and Core Principles Context Technical/phone screen for an Applied Scientist/Data Scientist role, ass...
Handle scope creep and teammate conflict
Behavioral & Leadership Two-Part Prompt (Data Scientist — Technical Screen) You will answer two behavioral prompts relevant to a data scientist role. ...
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...
Optimize precision–recall under class imbalance
You have extreme class imbalance (positive rate ~1%). You score 12 examples as follows (id, true_label, score): A,1,0.92; B,0,0.90; C,0,0.88; D,0,0.70...
Demonstrate leadership under strict rules
Behavioral — STAR: Operating Under a Non‑Negotiable Policy Context: Onsite behavioral & leadership interview for a Data Scientist. Describe a specific...
Explain core ML concepts and metrics
You are interviewing for a Data Scientist role. Answer the following ML fundamentals questions clearly and concisely. Concepts 1. Explain the bias–var...
Implement Batch Gradient Descent for Linear Regression
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Explain Propensity Score Matching and Assess Covariate Balance
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Evaluate Ensemble Models for Bias-Variance, Speed, and Interpretability
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