Data Analyst, who focuses on analyzing customer behavior data to identify trends but may not have the expertise to align ML metrics with business objectives.

Project Manager, who ensures the project is delivered on time and within budget but may lack the technical depth to define appropriate ML success metrics.

Data Quality Analyst, who ensures the data used for training the models is clean and reliable but is not primarily involved in setting success criteria.

Google Cloud Professional Machine Learning Engineer, who specializes in aligning ML success metrics with business problems, ensuring the models are designed to meet the specific goal of increasing customer engagement through measurable outcomes like click-through rates and conversion rates.

Both A and C, as together they cover the necessary aspects of data analysis and quality assurance required for defining success criteria.