•Design and implement a robust data pipeline for collecting, cleaning, and preparing relevant consumer financial data.

•Conduct exploratory data analysis to identify key features and patterns associated with financial distress.

•Develop and evaluate various machine learning algorithms

•Optimize model performance through feature engineering

•Interpret model results and translate complex statistical concepts into actionable insights

•Continuously monitor and improve model performance over time.

•Develop clear and concise documentation for the model development process.

•Stay up-to-date on the latest advancements in consumer credit modeling and machine learning.