Amazon Data Scientist Machine Learning Interview Questions
Practice the exact questions companies are asking right now.
"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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"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."
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"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."
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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...
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...
Apply Double ML with text-address features
Estimate the ATE of a First Reminder on CSAT via Double Machine Learning (DML) Context You have observational data on customer satisfaction (CSAT) sur...
Diagnose and fix underperforming ML model
Rapidly Improving Recall Under Class Imbalance (One-Day Plan) Context You inherit a binary fraud detection model with severe class imbalance (positive...
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 ...
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...
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...
Derive and compare core ML and RL methods
ML Fundamentals Technical Screen — Multi‑part Question Context: You are given a set of core machine learning topics to address rigorously. For each pa...
Design an ML Model for Interview Recommendation Pipeline
Scenario You are designing and deploying an ML model that mirrors a real-world recommendation pipeline serving a large product catalog with strict lat...
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...
Explain random forests, bagging, and evaluation
Random Forests, Bagging vs Boosting, and Practical Model Validation You are building a supervised learning model on tabular data. Explain and compare ...
Decide standardization, sparse numerics, correlated features
You are given a tabular dataset for supervised learning with features: F1 (counts, mostly small integers with many zeros), F2 (monetary amounts in dol...
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 fraud detection across channels with unknowns
Fraud Detection Strategy for a Multi‑Channel Marketplace Context: You are designing a fraud detection system for a large marketplace operating across ...
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...
Choose Models for Imbalanced Data and Time-Series Forecasting
Scenario You must choose and tune models for (a) forecasting marketplace demand with seasonality and trend, and (b) detecting fraud where the positive...
Build a package-allocation model for couriers
Automatic Package-to-Courier Assignment with ML + Optimization You previously assigned packages to couriers manually. Design an end-to-end system that...
Evaluate Ensemble Models for Bias-Variance, Speed, and Interpretability
Large-Scale Recommendation System: Ensembles, Overfitting, Metrics, Architectures, and Optimization Context You are designing a large-scale recommenda...
Design an Automated Home-Price Valuation Model
Scenario You are building an automated house-price valuation service for a real-estate platform. Question Design a home-price estimation system. Walk ...
Diagnose Bias–Variance Trade-off in Supervised Learning
Supervised Learning Review (Customer-Facing Ranking Context) You are designing and evaluating models for a customer-facing ranking service (e.g., orde...