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."
Choose Ranking Functions, Customer Value Metrics, and Predictive Models
Choose Ranking Functions, Customer Value Metrics, and Predictive Models A global e-commerce team asks three connected fundamentals: distinguish SQL ra...
Explain Transformer Components and Tree-Ensemble Trade-offs
Explain Transformer Components and Tree-Ensemble Trade-offs A technical discussion covers two foundations: how encoder and decoder components work in ...
Build and Defend a Baseline Model from a CSV
You receive a CSV during a live interview and are asked to build a useful predictive model. You may use code-completion or agent tools, but you must d...
Compare Logistic Regression and Random Forest in Python
Compare logistic regression and random forest for a binary classification problem implemented in Python. Cover preprocessing pipelines, regularization...
Explain Why Constant Neural-Network Initialization Fails
During neural-network training, what happens if every weight is initialized to 0? What happens if every weight is initialized to the same nonzero cons...
Explain How L1 and L2 Regularization Change Linear-Model Coefficients
Review a machine learning interview question comparing ordinary least squares with L1 and L2 regularization. The prompt focuses on coefficient behavio...
Predict Five-Minute Returns from Order-Book Data
You have time-stamped order-book observations containing buy and sell information, instrument, price, and quantity. Design a model and evaluation proc...
Analyze Temperatures and Update Regression
You are given historical daily temperature data for New York City and several nearby towns. Each row contains a date, the NYC temperature, and the tem...
Debug and fix a PyTorch Transformer training loop
Minimal Causal LM Debugging and Optimization You are given a tiny causal decoder-only language model implemented in PyTorch. It appears to "train" but...
Predict bike demand and avoid overfitting
You are given historical data for a city bike-sharing system. Available fields include station_id, hourly timestamp, number of bike pickups and return...
Design a Real-vs-Fake DNA Classifier
Question You are given DNA sequences over the alphabet {A, C, G, T}, where sequence lengths may vary. You have: - a small labeled dataset containing b...
How would you forecast bike demand?
This question evaluates a candidate's competency in time-series forecasting, feature engineering, model selection, and evaluation for short-horizon de...
Predicting the Next Elevator Call Location
This machine learning question tests the ability to design a predictive model for spatio-temporal demand forecasting, covering problem framing, featur...
Predict Stock Returns from Sentiment and Market Data
You have observations containing timestamp, stock identifier or index membership, sentiment score, relevance score, and stock prices. Design a model t...
Analyze Correlations and Generate Gaussians
You are interviewing for a quantitative data science role. Answer the following probability and simulation questions: 1. Let \(X\), \(Y\), and \(Z\) b...
How predict vehicles’ turn direction at intersection?
This question evaluates a data scientist's competency in time-series intent prediction at intersections, including label definition under ambiguity, t...
Explain Logistic Regression, Backprop, and Adam
Walk through the mathematical foundations that connect logistic regression to modern deep-learning training. The interviewer expects you to write the ...
Predict Bike Dock Demand
This question evaluates a data scientist's competency in time-series demand forecasting, covering temporal target definition, temporal feature enginee...
Explain Core ML Concepts
You are interviewing for a senior AI/ML-oriented Data Scientist role at a financial institution (J.P. Morgan). This is the "ML fundamentals" portion o...
Evaluate NLP Classification Models
You are interviewing for a Data Scientist internship at Amazon. The interviewer asks you to walk through how you think about an NLP classification pro...