Data Scientist Machine Learning Interview Questions
Practice 434 real Machine Learning interview questions for Data Scientist roles. From companies including Meta, Amazon, Google, Capital One, TikTok.
"I got asked a hardcore MCM DP question and I saw it on PracHub as well. Solved that question in 5 minutes. Without PracHub I doubt I could solve it in 5 hours. Though somehow didn't get hired, perhaps I guess I solved it too fast? /s"
"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."
"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."
"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."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
"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."
Optimize XGBoost for Predicting Marketing Outcomes
Optimize XGBoost for Predicting Marketing Outcomes Gradient-Boosted Trees for Marketing Outcome Prediction Context You’re building a model to predict ...
Design a Machine Learning Recommendation System Pipeline
Design a Machine Learning Recommendation System Pipeline System Design: End-to-End ML Recommendation System Scenario You are building an end-to-end ma...
How would you predict a car’s turning intention?
At an intersection, there are n vehicles stopped or approaching. For each vehicle, you have a short history (e.g., last 3–10 seconds at 10 Hz) of: - P...
Minimum Common Pairwise Correlation Among Seven Identically Distributed Random Variables
Suppose $X_1, X_2, \ldots, X_7$ are seven random variables defined on the same probability space. Each has mean $0$ and variance $1$, and they are ide...
Explain Feature, Model, and Validation Choices
This question evaluates a candidate's competency in end-to-end machine learning project execution, including data processing workflows, feature creati...
Address Overfitting with L1 Regularization in Regression
Linear Regression with Many Predictors and Few Observations You fit an ordinary least squares linear regression with 500 predictors and 600 observatio...
Explain Linear Regression to Non-Technical Stakeholders
Explain Linear Regression to Non-Technical Stakeholders You are explaining core machine-learning concepts to non-technical stakeholders during a proje...
Design a Ride-Hailing ETA System
You are a Data Scientist at a ride-hailing company. Design an ETA system used in the rider and driver apps to estimate both pickup ETA and trip ETA. D...
Compute gambler’s ruin probabilities and hitting times
This question evaluates understanding of stochastic processes, Markov chains, and discrete-time random walks by requiring derivation of absorption pro...
Solve a constrained problem using KKT conditions
This question evaluates understanding of constrained optimization using Karush–Kuhn–Tucker (KKT) conditions, including Lagrangian formulation, station...
Design a Low-Latency Store Recommender
This question evaluates system design and machine learning competencies for real-time, low-latency store recommendation systems, including retrieval, ...
Diagnose overfitting from error curves
You are evaluating a supervised machine learning model. You are shown a plot where the x-axis is training epoch or model complexity and the y-axis is ...
Design bot detection and evaluate trade-offs
Bot-Detection System Design for Comment Activity Context You are designing and evaluating a machine learning system to detect automated (bot) comment ...
Present and defend your data challenge end-to-end
10–12 Minute Interviewer-Driven Walkthrough: Recent Data Challenge Provide a concise, structured walkthrough of a real project you led end-to-end. Ass...
Find companies similar to a given client
System Design: Retrieve Top-20 Most Similar Companies for Sales Prospecting You are given an anchor client (e.g., The Coca‑Cola Company). Design a sys...
Estimate b when features exceed samples
Consider the linear model y = Xb + ε with X ∈ R^{n×(m+1)} including an intercept. a) Derive the OLS estimator b̂ = (XᵀX)^{-1}Xᵀy, stating the rank con...
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...
Detect leakage and evaluate a prediction model
Churn Prediction Model: Leakage, Validation, KPIs, Interpretation, Monitoring Context: You inherit a weekly-scored model that predicts whether a user ...
Detail NLP preprocessing and n‑gram choices
Describe your text preprocessing pipeline given the source modality: typed text, scanned/handwritten OCR, or speech-to-text. Specify language handling...
Diagnose location-sorted recommender causing revenue drop
This question evaluates skills in diagnosing production recommender systems, causal inference and experimentation, multi-objective ranking and safe ex...