Automated Credit Risk Scoring Model with Pandas Regression

Develop a Python script that imports loan application data from a Google Sheet, performs multi-variable logistic regression for credit risk assessment, and generates a predictive scoring model. The script should handle missing data, perform feature engineering, and output a probability of default for each applicant. Include visualizations of feature importance and model performance metrics using seaborn and scikit-learn.