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."
Justify all-cash compensation expectations and trade-offs
All-Cash Compensation Expectation (Data Scientist — HR Screen) Context You are in an HR screen for a Data Scientist role. Provide a clear, well-resear...
Demonstrate JD skills with quantified outcomes
Data Scientist HR Screen: Map a JD Skill to Your Resume Project Pick one skill explicitly highlighted in the job description and one project from your...
Describe handling pressure and stakeholder conflicts
Behavioral/Scenario Questions for a Data Scientist — Technical Screen Answer concisely using STAR (Situation, Task, Action, Result) where relevant. 1....
Build an uplift model for targeting
Flu-shot Campaign: Treatment-Effect Modeling and Targeting Policy You have historical campaign logs from last season that include randomized holdouts....
Diagnose metric drop in Ads Manager
Investigate a 15% Drop in Ad-Creation Completion Rate Context On 2025-06-10, your Ads Manager dashboard shows a 15% relative decrease in the ad-creati...
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...
Analyze HT vs HH stopping-time probabilities
Coin-Flip Stopping Game: HT vs HH You repeatedly flip a coin until either the pattern HT appears (Player A wins) or the pattern HH appears (Player B w...
Design a Cold-Start-Aware Recommender
System Design: Two-Stage Recommender for a New Content App Context You are designing recommendations for a new content app with sparse interactions an...
Explain why join C1 and your impact
Why Capital One (C1)? Behavioral/Leadership Prompt for a Data Scientist Task Provide a concise, evidence-based answer that: 1. Gives 2–3 specific, ver...
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...
Model session times and comments with exponential/Poisson
Session Duration Memoryless Assumption and Poisson Comment Counts Setup - We model user session end times with a constant hazard (memoryless) over tim...
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 a production face recognition system
Design an On-Device Face Recognition System for Mobile Access Control Context You are designing a face-based access control system for mobile devices ...
Lead XFN decision under tight timeline
Scenario: 72-Hour VP-Level Recommendation on Expanding a New Quoting Workflow You have 72 hours to deliver a VP-level deck recommending whether to exp...
Define success metrics for Instant Book
Instant Book: Metrics, Measurement, Rollout, and Risk Plan Context You are evaluating an "Instant Book" feature that allows customers to immediately b...
Implement R² and Compare PCA With/Without Scaling
NumPy-only implementation: R² and PCA (Data Scientist take-home) Implement from scratch using only NumPy (no scikit-learn). Use float64 throughout and...
Diagnose a 20% retail revenue drop
E-commerce Revenue Drop Diagnosis Case Context Week T net revenue is down 20% versus the prior 4-week moving-average baseline. You have weekly e-comme...
Design an A/B test; choose Z vs T
A/B Test on a Signup Funnel: Sample Size, Test Choice, Sequential Design, and Causal Plan Context You are planning a two-variant A/B test on a signup ...
Design an experiment with marketplace network effects
Causal Experiment Design for a Two‑Sided Marketplace with Interference You are designing a causal experiment for a new networked product in a two‑side...
Validate DID and IV assumptions rigorously
Causal Inference and IV: DID, TWFE, Staggered Adoption, Clustering, and 2SLS Context: You are analyzing the causal effect of a reminder on an outcome ...