Describe a Machine Learning Project You've Led: This question helps gauge your practical experience and understanding of the end-to-end process, including problem framing, data collection, model selection, evaluation, and implementation. How Do You Handle Data Cleaning and Preprocessing? Demonstrates your expertise in handling real-world data, identifying missing values, outliers, and ensuring data quality before analysis. Explain a Complex Statistical Concept in Layman's Terms: Assesses your ability to communicate technical concepts to non-technical stakeholders, indicating your capacity to bridge the gap between data science and business objectives. Walk Us Through Your Approach to Feature Selection: Highlights your knowledge of selecting relevant features and reducing dimensionality, showcasing your ability to improve model performance and interpretability. Discuss Ethical Considerations in Data Science: Shows your awareness of ethical implications in data collection, analysis, and model deployment, indicating your commitment to responsible and unbiased data practices.