Machine Learning Engineer + Data Scientist + Software Engineer Interview Questions
Practice the exact questions companies are asking right now.
"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."
Assess education–income effect credibly
This question evaluates a data scientist's competencies in causal inference, experimental design, model selection, estimand specification (ATE) and se...
Handle p≈n linear regression with L1
This question evaluates competence in high-dimensional linear regression, penalized estimation (L1/L2/elastic net), preprocessing and feature handling...
Demonstrate leadership under ambiguity
Describe a time you faced an open-ended, lightly guided interview or project where the counterpart had a strong accent and offered little direction. H...
Compute sample sizes and error control
Using the Biker experiment context, compute required sample sizes and describe error control under practical constraints. Show formulas and numeric an...
Deploy multi-armed bandits safely
Online bandit with 3 variants, churn guardrail, and delayed conversions Context You are running an online experiment with 3 variants (including contro...
Choose and compute recommender evaluation metrics
Restaurant Recommender: Offline Evaluation and Modeling Context: You are scoring p(y=1|x) with logistic regression to predict if a user will engage wi...
Handle highly imbalanced classification data
You must build a binary classifier for fraud with a 0.2% positive rate and 10M rows × 500 features. Propose an end-to-end plan that covers: 1) data sp...
Measure causal impact of YouTube ads
This question evaluates causal inference and experimental design skills for marketing measurement, including competency in identifying confounders, de...
Explain Random Forest randomness and implications
Random Forest — Rigor and Practical Choices Context: You are building a binary classifier with a Random Forest. The dataset has 100,000 rows, 100 feat...
Diagnose uplift drop in email A/B tests
Personalized Product Emails Experiment — Design, Sizing, and Debugging Conflicting Reruns Context An e-commerce company plans to A/B test personalized...
Diagnose unbiasedness in a messy A/B test
This question evaluates a data scientist's ability to diagnose unbiasedness of an intent-to-treat (ITT) estimator in A/B testing under noncompliance, ...
Design an A/B test for pinned-unread feature
Experiment Design: Evaluating a Pinned-Unread Chat Feature Context You are evaluating a new messaging feature that pins chats with unread messages to ...
Choose clustering vs regression; explain KNN
When would you use clustering vs. regression on a business problem with partially labeled outcomes? Specify the decision criteria (label availability,...
Interpret regression metrics and assumptions
A multiple linear regression is fit to predict arrival delay with standardized numeric predictors and one‑hot categorical variables. Without seeing th...
Diagnose and interpret regression assumptions
This question evaluates proficiency in regression diagnostics and model selection for count outcomes, including OLS assumption checks, log-transformat...
Decide when to model courier ETA
This question evaluates a candidate's competency in machine learning product decisions—covering target definition, dispatch-time feature design, offli...
Compute optimal stopping in a die-rolling game
Optimal stopping with a fair die (3-roll horizon) You observe outcomes of fair six-sided die rolls (faces 1–6) and may stop after any roll to take the...
Explain power drivers and resolve unexpected A/B results
A/B Testing: Power, Sample Size, Allocation, and Diagnostics You are analyzing a two-proportion (binary conversion) A/B test with independent users, n...
Design and evaluate an A/B test for launch
A/B Test Design: New Matching Model for a Two‑Sided Marketplace Context You are testing a new matching/ranking model that determines which providers a...
Compute averages and binomial/Poisson probabilities
Streaming Mean and Binomial vs Poisson Approximation Part A — Streaming Mean Update You have an existing dataset of N = 1,000 observations with mean 1...