If you’re a data scientist on a product team, much of your work involves getting a product ready for release. You may conduct exploratory data analyses to understand your product’s market, or build the data models and pipelines needed to power a new product feature, or design a machine learning model to unlock new product functionality. But your work doesn’t end once a product goes live. After a product is released, it’s your job to help identify if your product is a success.