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."
Design a fintech homepage ranker
Personalized Product Ranking for a Fintech Home Page — End-to-End Design Context You are designing a personalized ranking system for a fintech app’s h...
Compute fraud probabilities with Bayes and Binomial
Fake-Account Detection with Binomial Sessions and Bayes Updating You are evaluating a rules-based detector for fake accounts on an online platform. Ea...
Measure fake-news interventions under network interference
Experiment Design Under Interference: Warning Label for Suspected Fake-News Reshares Context You are testing a pre-reshare warning label for links sus...
Design a data platform enablement
Design a pragmatic data‑platform enablement for a mid‑tier retail bank migrating to cloud under PII and data‑residency constraints. Describe the targe...
Design and analyze email deliverability experiment
This question evaluates a data scientist's competency in experimental design, causal inference, sequential testing (frequentist and Bayesian), instrum...
Derive logistic regression objective and gradients
Context: Binary Logistic Regression You are given a binary classification dataset {(x_i, y_i)}_{i=1}^m with labels y_i ∈ {0, 1}. The model uses the si...
Demonstrate cross-functional leadership with data and reflection
Cross-Functional Project Under a Hard Deadline (Data Scientist) Context: Share one concrete project where you partnered across at least three function...
Evaluate a model and choose metrics
Fraud-screening model evaluation under class imbalance and asymmetric costs Context You operate a binary classifier that flags e‑commerce orders for m...
Drive product decisions with causal product sense
Experimenting on a New Paywall with Likely Spillovers Context You are designing an experiment to evaluate a new paywall on a social/content app where ...
Design a model for imbalanced conversions
Predicting Purchase Propensity After a Campaign (5% Positives) You previously ran a marketing campaign to 10,000 customers and observed 500 purchases ...
Design and power a frequency-cap experiment
Experiment Design: Raising a 7‑Day Frequency Cap from 3→4 Impressions Context A large video ad campaign plans to raise the per‑user rolling 7‑day freq...
Count queen attacks on points with blockers
You are given positions on an (unbounded) 2D integer grid. - queens: coordinates of queens - points: query coordinates A queen attacks along 8 directi...
Validate whether a binary string is good
You are given a binary string s consisting only of characters '0' and '1'. Define a good string recursively by the grammar: - '0' is a good string. - ...
Solve array merge, tree view, and maze tasks
This question evaluates array manipulation and in-place algorithms, binary tree traversal and visibility reasoning, and grid graph traversal for path ...
Design recommendation and weapon-ad detection systems
This question evaluates proficiency in end-to-end ML system design, covering scalable recommendation systems and safety-focused ad classification with...
How would you handle conflict and data pressure?
Behavioral questions (answer both) 1) Leading amid collaborator disagreement You are newly assigned as the team lead by your manager. One collaborator...
Describe overfitting and L1/L2 regularization
Define overfitting in machine learning and explain why it is harmful. Then describe L1 and L2 regularization: - How each one modifies the loss functio...
Explain the bias–variance trade-off
Explain the bias–variance trade-off in supervised learning. In your answer, cover: - What bias and variance mean in the context of a prediction model....
Generate all safe queen placements on board
You are given an integer n representing the size of a chessboard (n × n). You need to place n queens on the board so that no two queens attack each ot...
Explain debugging methodology for production issues
In a technical interview, you are asked: > What is your methodology when debugging or when something goes wrong? Describe a systematic approach you wo...