New Grad Data Scientist 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 Uber Eats Restaurant Recommendations
This question evaluates a candidate's ability in end-to-end machine learning system design for personalized restaurant recommendations in a food-deliv...
Compute the Probability for Two Uniform Variables
Let \(X\) and \(Y\) be independent random variables, each uniformly distributed on \([0,1]\). Define: - \(L = \max(X,Y)\) - \(S = \min(X,Y)\) What is ...
Evaluate marketplace interventions
This question evaluates a data scientist's competency in product analytics, causal inference, and experimentation design for two-sided marketplaces, f...
Can one car serve all riders?
This question evaluates understanding of interval scheduling and conflict detection, testing skills in time-interval reasoning, sorting, and efficient...
Build cold-start restaurant ratings
This question evaluates a data scientist's ability to design a production-ready predictive modeling approach for cold-start ratings, testing competenc...
Describe resolving a conflict with a teammate
You are interviewing for a Data Scientist PhD Summer Intern role. Tell me about a time you had a conflict with a teammate on a research or data/ML pro...
How to deploy and tune multimodal models?
Question You are interviewing for a new-grad machine learning / data scientist role at ByteDance. Answer the following related machine-learning and LL...
Describe Conflict and Impact
Prepare strong answers for the following behavioral and project deep-dive questions for a data scientist role: 1. Tell me about a time you went beyond...
Predict driver acceptance
This question evaluates a candidate's competency in designing and operationalizing an end-to-end machine learning solution for predicting driver accep...
Evaluate Promotions for Uber Eats Users
This question evaluates a data scientist's causal inference and experimentation competencies—including randomized trial design, treatment-effect estim...
Implement KNN from Scratch
This question evaluates a candidate's understanding and practical implementation skills for instance-based supervised learning, specifically the k-nea...
Explain KNN and PCA and key tradeoffs
In a Data Scientist internship interview, you are asked ML fundamentals: 1) K-Nearest Neighbors (KNN) - Explain how KNN works for classification and r...
Should Uber double member discounts?
This question evaluates competency in causal inference, experimental design, statistical power and sample-size analysis, metric definition, and two-si...
Implement FizzBuzz
This question evaluates a candidate's ability to implement basic control flow, use modulo operations, iterate over sequences, and reason about time an...
Describe ownership and failure
Answer the following behavioral questions in a structured way, using specific examples from your past work or research: 1. Tell me about a time you we...
Evaluate shift from branch to digital channel
Business case: OneMain credit card — branch vs. digital acquisition OneMain runs a credit-card business with two acquisition/servicing flows: - Tradit...
Evaluate Marketplace Changes
This question evaluates a data scientist's competency in experimental design, causal inference, metrics instrumentation, A/B testing, and marketplace ...
Compute and plot a precision–recall curve
You are given model outputs for a binary classifier: - y_true: an array of 0/1 ground-truth labels of length n. - y_score: an array of predicted score...
Explain Overfitting and Transformer Basics
This question evaluates proficiency in core machine learning competencies such as overfitting and generalization, selection and regularization of loss...
Evaluate a cold-start rating launch
This question evaluates a data scientist's competency in marketplace analytics, causal inference, experimentation design and measurement, specifically...