The difference between trivia and meaty knowledge is somewhat contextually dependent, but an understanding of how core probability and statistics concepts are integrated into the framework of machine learning by means of linear algebra and the other analytical tools is pretty damn useful to have substantive conversations about ML design decisions. Helps when everyone in the team speaks that language to keep up the momentum.