Data Scientist Machine Learning Interview Questions
Practice 399 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."
Implement NumPy neural-network layers
You are given a neural-network coding task in NumPy. Let X be a batch input matrix of shape (B, d_in), W a weight matrix of shape (d_in, d_out), and b...
Engineer and Impute ZIP Features
Question You are building a predictive model for a product team. For some users you have address fields such as street, city, state, and ZIP code. Man...
Explain Chunking for Financial RAG
Suppose you are building a retrieval-augmented generation (RAG) assistant over long financial research reports, filings, and policy documents. Explain...
Explain ROC-AUC vs PR-AUC tradeoffs
Question You trained a binary classifier that outputs predicted probabilities. Compare ROC-AUC and PR-AUC (the latter usually reported as Average Prec...
Design Siri-vs-GPT query routing
You are a Data Scientist at Apple designing a feature that decides whether a user's natural-language query should be routed to Siri or to a GPT-based ...
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...
Build House Price Model Responsibly
You are asked two machine-learning questions. Part A: House-price prediction Using a cleaned housing dataset with target sale_price, describe an end-t...
Design robber detection from surveillance video
You’re a Data Scientist on a team building a computer-vision system for public-safety monitoring. Problem Design an ML system that uses fixed surveill...
Compare two rare-event detection models statistically
You are evaluating two models (Model A and Model B) for rare-event detection (e.g., fraud, abuse, medical adverse event). Positives are extremely rare...
Compute Random Walk Hitting and Return Probabilities
Consider simple symmetric random walks on integer lattices. 1. In one dimension, a particle starts at integer position x with absorbing boundaries at ...
Predict driver acceptance
Design an end-to-end machine learning approach to predict driver acceptance probability in a ride-sharing or delivery marketplace. Assume that when a ...
Implement Streaming Clustering for Numbers
You receive a continuous stream of numeric values. Choose an appropriate clustering algorithm and implement it so that each incoming number can be ass...
Implement K-means and handle train-inference mismatch
Part A — K-means (implementation + concepts) You are given a dataset \(X \in \mathbb{R}^{n \times d}\) and an integer \(k\). 1. Explain K-means: what ...
Predict Bike Dock Demand
You are working on a docked bike-sharing system. Build a model that predicts how many bikes will be checked out from a specific dock in the next hour....
Analyze trading RFQ competitiveness data
RFQ Competitiveness Analysis in Excel You are given an Excel file containing a few months of trading RFQ (request-for-quote) data for a sales & tradin...
How to rank statements by likelihood
You are given a "likelihood" / "data interpretation" test. For each question: - You are shown a data representation (e.g., a large table, a scatter pl...
Design and diagnose a regression pipeline
CLV_90 Prediction Pipeline under Zero-Inflation, Heavy Tails, and Multicollinearity Context You need to predict 90-day customer value (CLV_90) at the ...
Model flight delays with EDA and explanation
Predicting 15+ Minute Arrival Delays at Scheduled-Departure Time You are building a binary classifier that predicts whether a domestic flight will arr...
Design and evaluate a RAG system
You are interviewing for an L5 Data Scientist role focused on LLM applications. Design a retrieval-augmented generation (RAG) system for an internal q...
How to validate production models?
You are interviewing for a fintech model-validation team that acts as a second line of defense for credit-risk and fraud models. A hiring manager asks...