Data Scientist Machine Learning Interview Questions
Practice 398 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."
Which clustering algorithm would you use and why
Question You need to cluster users for a social product (e.g. Meta) to discover meaningful groups such as communities, interest groups, or usage segme...
How to deploy and tune multimodal models?
Question You are interviewing for a new-grad machine learning / data scientist role at ByteDance. Answer the following related machine-learning and LL...
Derive correlation bounds and omitted-variable bias
Core Statistics Prompt Answer the following related statistics questions. Part A — Pairwise correlation constraints Let \(X, Y, Z\) be random variable...
Build a fair loan classifier
You are given a dataset of loan applicants. Each row represents one loan application and contains applicant attributes, loan attributes, and a binary ...
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...
Handle imbalance, validate samples, and avoid overfitting
Answer the following applied ML questions. 1) Class imbalance You’re building a binary classifier where positives are rare. - What are practical ways ...
Evaluate OutlierHandler Class for Code Quality and Testing
Code Review: OutlierHandler and Imputer Classes Context You are given a Python module that implements one OutlierHandler class and three Imputer class...
Choose threshold under asymmetric costs
You own a credit-card fraud classifier deployed as a probability scorer. Choose an operating threshold under asymmetric costs and justify it quantitat...
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...
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...
Build and evaluate bad-link classifier
You have 1,000 URLs labeled as bad or good and a much larger unlabeled pool, with bad links rare. Design features and train a logistic regression. Exp...
Diagnose outliers and influence in linear regression
OLS Diagnostics: Outliers, Leverage, Influence, and Cook's Distance Context You are fitting an ordinary least squares (OLS) linear regression with an ...
Extract companies from noisy text
Extracting Company Names from Noisy Resumes and Web Snippets Context You receive messy resume text (PDF-to-text/OCR, varying casing) and scraped web s...
Minimize max L1 radius with k centers in 1D
You are given an array A of n integers (values may be negative and may repeat) and an integer k (1 ≤ k ≤ n). Place k cluster centers anywhere on the r...
Design enterprise file recommendations under ACLs
Design a system to recommend to a signed-in enterprise user the next files they are most likely to open in a productivity suite. Cover: (1) key signal...
Contrast Lasso vs Ridge trade‑offs
Regularization choices for modeling contribution per order (p=50) Context: You are building a linear model for contribution per order (continuous outc...
Diagnose and fix flawed model fit
Fixing a Churn Classifier: Encoding, Imbalance, Evaluation, and Fairness Context You inherit a binary classifier that predicts churn=1. The current im...
Build predictive model for feature rollout targeting
Before global launch, you want to predict which users or products would benefit most from the 'More like this' button so you can stage rollout. Design...
Design and validate a cost-sensitive classifier
Binary Purchase Prediction with Delayed Labels and Imbalanced Classes Context - Goal: Ship a real-time binary classifier that predicts whether a user ...
Design a hierarchical MF delinquency forecasting system
Forecasting 90+ Day Delinquency Rates for Multifamily Loans: Hierarchical, Leakage-Safe System Design Context You need to forecast 90+ day delinquency...