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."
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...
Compute sample size and significance
You are planning a two-variant A/B test with equal allocation and a binary primary metric (conversion). Baseline rate p0 = 0.045. You want to detect a...
Diagnose and fix linear regression assumption breaks
OLS Assumptions, Diagnostics, Remedies, and Refitting Under Heteroskedasticity and Multicollinearity You are fitting a linear regression with Ordinary...
Explain and tune XGBoost; prevent overfitting
XGBoost Tree Booster: Objective, Hyperparameters, Tuning for Imbalanced Detection, and Post-training Use Context: You are building a binary classifier...
Design rigorous A/B test and causal analysis
Experiment Design and Causal Inference: Multi-part Problem Context: You are designing a high-traffic web A/B test on a binary conversion metric. Answe...
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...
Design theme-park profit model and bid decision
Theme Park Pricing and Land-Acquisition Case Context You manage pricing analytics for a Disney-like theme park. Baseline demand is steady. A land auct...
Optimize red-ball draw probability, prove optimality
This question evaluates probabilistic reasoning, optimization and mathematical proof skills by asking how to allocate red and blue balls across two bo...
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...
Design A/B test for credit card offer
A/B Test Design: New Credit-Card Acquisition Flow (Revised APR Disclosure + Signup Bonus) Context You are launching a new credit-card acquisition flow...
Design and critique an abuse-detection ML system
This question evaluates system-design and production machine learning competencies including large-scale classification versus risk scoring, handling ...
Design and analyze a card signup A/B test
A/B Test Design: Co‑Branded Gym Credit Card Offer Context: You will A/B test a 3‑month free gym membership offer shown on the application landing page...
Diagnose overloaded Kubernetes cluster
Kubernetes Overload: End-to-End Debug + Mitigation Plan You are given a Kubernetes-based microservices system that is currently overloaded, exhibiting...
Design a Production-Ready URL Shortener
System Design: Production-Ready URL Shortening Service Goal Design a production-ready URL shortening service that can issue short links, resolve them ...
Whiteboard and Deep Dive a Past Project
System Design: End-to-End Architecture Walkthrough Prompt Whiteboard the end-to-end architecture of a complex, user-facing system you led. Cover: 1. M...
Find Shortest Paths in Road Network
You are reviewing code for a road-network graph. The domain objects are: `java class Location { String name; Location(String name) { this.name...
Explain mixed models and fixed vs random effects
In an applied DS setting, you are modeling an outcome (e.g., watch time per session, conversion, or rating) across multiple entities (e.g., users, cre...
Explain leakage, missing data, and common losses
This question evaluates a candidate's understanding of data leakage, strategies for handling missing data, and the differences between loss functions ...
Implement K-means clustering from scratch
This question evaluates a candidate's understanding of clustering algorithms and practical implementation skills in unsupervised machine learning, inc...
Explain overfitting vs underfitting and fixes
This question evaluates understanding of model generalization in supervised machine learning, focusing on the concepts of overfitting and underfitting...