A telecommunications company is experiencing high customer churn and wants to leverage machine learning to predict which customers are likely to churn. The company has a diverse dataset including customer usage patterns, service complaints, and billing history. The project team includes a Customer Support Representative, a Software Developer, a Business Analyst, and a Google Cloud Professional Machine Learning Engineer. Given the complexity of the dataset and the need for accurate predictions, which two roles are most critical in determining whether the problem should be approached as a classification, regression, or clustering task? Choose two correct options.