I've interviewed several people for machine learning/data science positions and I've found when people don't get the math behind machine learning they don't get the machine learning. Math, specifically linear algebra, is the language that lets you move from our 2/3 dimensional thinking to a more abstract high-dimensional space: the one machine learning lives in. It's easy to draw a bunch of points on a piece of paper and then draw a line between it and say "this is linear regression!" It's much harder to argue why regularization is important and why/how you would want to use/tweak it. The math is essential to getting important aspects of machine learning like this.