Artificial Intelligence for Marketing Questions

Understanding how artificial intelligence and machine learning enable marketing use cases and personalization at scale. Candidates should cover model types used for prediction recommendation and clustering data and feature design for marketing signals training and evaluation strategies offline and online validation and controlled experiments such as A and B testing model serving and inference latency trade offs for real time activation machine learning operations practices for deployment monitoring and retraining and responsible use topics such as fairness explainability and privacy preserving techniques. Interviewers probe the ability to translate model outputs into measurable marketing outcomes and to balance model complexity with operational cost.