5 common causes of friction between data scientists and the rest of the stakeholders

As a data scientist, have you ever been frustrated that your stakeholders don't see the value that you bring to the table? You may ask yourself, "How far should I go in explaining the work I do or what my models are doing?" If that sounds like you, then pay close attention to this post and the next, as they are all about improving collaboration between data scientists and other stakeholders. This is a two-part post: This article covers underlying assumptions and gaps in understanding that cause friction between data scientists and stakeholders; my other article, offers concrete steps for better collaboration. Machine Learning (ML) models are inherently complex and hard to explain.