Citadel Machine Learning Interview Questions
Practice the exact questions companies are asking right now.
"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."
"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 outliers and influence in linear regression
OLS Diagnostics: Outliers, Leverage, Influence, and Cook's Distance Context You are fitting an ordinary least squares (OLS) linear regression with an ...
Estimate OLS via streaming sufficient statistics
Streaming OLS and Ridge for Out-of-Core, High-Dimensional Linear Regression You need to estimate linear regression coefficients when the dataset is to...
Design city home-price prediction system
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Explain factor leakage checks and IC/ICIR filtering
You’re interviewing for a quantitative/alpha role and have built predictive factors (features) for returns. Answer the following (conceptual) question...
Make a hard MoE router differentiable
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Explain RF optimization and variable-importance pitfalls
Optimize and Regularize a Random Forest Regressor for Tabular Data Context: You are training a Random Forest (RF) regressor on tabular data and need t...
Build a baseline linear regression pipeline
Task: Baseline Linear Regression Pipeline (Python) Context You are given a tabular dataset in a pandas DataFrame df. The goal is to predict a continuo...
Design regression and classification ML pipelines
Take‑Home: Two End‑to‑End ML Workflows on Tabular Data Objective Design and implement two complete machine learning workflows on tabular data (typical...
Design Framework for Robust House-Price Prediction Model
Model Robustness, Diagnostics, Random Forests, and Large-Scale Regression Context You are building and evaluating a supervised model to predict reside...