I've seen this pattern frequently on a few data science teams. However, I do think there is a lot of value to data science, but it more has to do with incorpor

I've seen this pattern frequently on a few data science teams. However, I do think there is a lot of value to data science, but it more has to do with incorporating metrics and accountability rather than modeling. For example, I've seen many mission-critical rules-based systems with no accuracy metrics. A data scientist is asked to beat this system using machine learning and fails miserably because the rules were developed by experts over years and the data scientist has a month and is only a few years out of grad school. However, in the process of building the model that data scientist built data pipelines for measuring the rules-based system's accuracy and fixed a small number of major data integrity issues. Unfortunately this isn't considered a win and the data scientist usually leaves the company soon after. :shrug: