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."
Evaluate Promotions for Uber Eats Users
Uber Eats wants to send promotions or coupons to its users (for example, "$5 off your next order" or "20% off, minimum basket $15"). You are the data ...
Design Uber Eats Restaurant Recommendations
Design a restaurant recommendation system for the Uber Eats home page. A user opens the Uber Eats app and should see a ranked feed of restaurants avai...
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...
Build cold-start restaurant ratings
Uber Eats wants a cold-start rating system for newly onboarded restaurants before they accumulate enough real reviews. You are asked to design the mod...
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...
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...
Evaluate a cold-start rating launch
Uber Eats is considering showing an initial rating for newly onboarded restaurants that have little or no historical review data. This is a two-sided ...
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 ...
Should Uber double member discounts?
Uber is considering increasing the member discount on rides from 5 percent to 10 percent. This can affect rider demand, driver supply, marketplace bal...
Evaluate marketplace interventions
You are a data scientist at a two-sided delivery marketplace. Answer the following product analytics and experimentation cases. For each case, define ...
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...
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...
Can one car serve all riders?
Given a list of passenger waiting intervals, determine whether a single car can serve all passengers without any scheduling conflict. Each interval is...
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...
Model Driver Acceptance Probability
Design a machine learning system to predict the probability that a driver accepts a trip or delivery offer. Your answer should cover: - the prediction...
Evaluate Marketplace Changes
You are a marketplace data scientist at a mobility and delivery platform. Discuss how you would evaluate the following product and algorithm changes: ...
Compute CDF from a PDF Function
You are given a callable function pdf(t) that returns the probability density of a normal distribution at value t. Implement a function cdf(x) that re...
Implement FizzBuzz
Implement the classic FizzBuzz problem. Given a positive integer n, return the sequence from 1 to n as strings with the following rules: - If a number...
Explain Overfitting and Transformer Basics
Answer the following machine learning questions in a self-contained way: 1. What is overfitting? How would you recognize it from training and validati...
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...