Build a baseline linear regression pipeline
Company: Citadel
Role: Data Scientist
Category: Machine Learning
Difficulty: medium
Interview Round: Technical Screen
Build a baseline linear regression pipeline in Python without code-completion tools: split the data into train/validation sets with a fixed random seed, impute missing values, one-hot encode categorical features, scale numeric features, train an ordinary least squares model, and evaluate it using RMSE and R^2 on the validation set while avoiding data leakage (fit transformers only on training data). Output the fitted coefficients, key metrics, and a brief interpretation of results.
Quick Answer: This question evaluates a candidate's ability to construct a leakage-safe preprocessing and modeling pipeline for tabular data, including imputation, categorical encoding, feature scaling, ordinary least squares linear regression, and interpretation of coefficients and performance metrics.