Design a house-price prediction model

Company: Two Sigma

Role: Data Scientist

Category: Machine Learning

Difficulty: easy

Interview Round: Technical Screen

Quick Answer: This question evaluates machine learning and data science competencies including regression model design, feature engineering, data-splitting and leakage prevention, selection of evaluation metrics, handling missing values, outliers and high-cardinality location features, temporal drift management, and model interpretation for house-price prediction. It is commonly asked in the Machine Learning domain to assess end-to-end practical application and conceptual understanding of validation and metric trade-offs, primarily testing practical application supported by conceptual reasoning and stakeholder communication.