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."
How Would You Test Whether Momentum Is a Real Alpha Signal in Stocks?
In a quantitative-research data-analysis round, you are asked a methodology question. No coding is required — the interviewer wants you to reason like...
Bounds on the Probability of Rain on at Least One Weekend Day
The probability that it rains on Saturday is $p$, and the probability that it rains on Sunday is $q$. Nothing is said about whether the two days are i...
Explain Overfitting and Transformer Basics
This question evaluates proficiency in core machine learning competencies such as overfitting and generalization, selection and regularization of loss...
Analyze trading RFQ competitiveness data
This question evaluates a candidate's skills in exploratory data analysis, Excel-based feature engineering, basic statistical modeling, and interpreta...
Build a leak-free sklearn churn pipeline
Take‑Home ML Task: Reproducible Subscription Classification Pipeline You are given a daily user-level dataset and must build a reproducible Python (sc...
How to forecast bike dock demand
This question evaluates competency in time-series forecasting and demand prediction, including feature engineering, model selection and evaluation, ha...
Handle imbalance, validate samples, and avoid overfitting
This question evaluates competencies in handling class imbalance, choosing and interpreting evaluation metrics and decision thresholds, validating sam...
Design a robust conversion propensity model
Daily Notification Propensity Model (Top-20% Targeting) Context You need to score users once per day with the probability they will make a purchase wi...
Build a regularized regression pipeline
Technical Screen: End‑to‑End Signup Prediction with scikit‑learn Context You are given a cleaned tabular dataset with marketing and product metrics. Y...
Explain KNN and how to tune it
K-Nearest Neighbors (KNN) fundamentals You are interviewing for a Data Scientist role. 1. Explain how the KNN algorithm works for both classification ...
Explain linear regression to non‑technical stakeholders
This question evaluates understanding of linear regression fundamentals and related competencies, including defining target, features, coefficients, i...
Design a robust fraud detection system
Real-Time Card Fraud Detector — End-to-End Design Context - Fraud base rate ≈ 0.2% (severe class imbalance) - Labels arrive with a 14-day delay (e.g.,...
Design multimodal deployment under compute limits
You need to answer a set of questions related to multimodal model deployment and post-training optimization in an interview. Provide systematic explan...
Design a Homepage Store Recommender
This question evaluates system-level machine learning and recommender competencies, including candidate retrieval, filtering and ranking, feature-stor...
How to validate production models?
This question evaluates a candidate's competency in production model validation, covering model risk assessment, data and label quality, time-dependen...
Interpret AUC Values and Handle Class Imbalance Techniques
Interpret AUC Values and Handle Class Imbalance Techniques AUC and Class Imbalance in Binary Classification Context You are evaluating a binary classi...
Market-Making Estimation Game: Optimal Confidence-Interval Strategy Over 5 Rounds
You are interviewing with a proprietary trading firm, and one of the rounds is a market-making game played over 5 rounds. In each round, the interview...
How would you build and evaluate a classifier?
This question evaluates a data scientist's proficiency in binary classification model evaluation, end-to-end machine learning project design, and mode...
Build and evaluate illegal-video classifier
This question evaluates competency in end-to-end Machine Learning system design, including multimodal modeling (vision, audio, text), data engineering...
Diagnose and fix flawed model fit
This question evaluates a data scientist's competency in applied supervised learning diagnostics, including feature encoding, feature scaling, class i...