
The data PM understands the technological infrastructure involved in building products at a technical level. What kind of infrastructure is needed to support the product? Do machine learning models need to be scored in real-time or can they be prescored offline? What is the plan for retraining models on new data? How will the model’s success be evaluated over time? What is the complexity cost for implementing the model in production? Yes, data scientists will be answering these questions as well, but the data PM needs to be an active participant in these discussions as part of the inevitable tradeoffs involved in product development.