I do believe 100% data science degrees are a money grab. Lately I’ve been playing devils advocate and thinking maybe they are more practical than statistics degrees for data science positions.

Couple of reasons if you are good at utilizing python based models and libraries to validate your data and results, how much more value to your job would a statistics degree truly add?

Coming from a computer science background it was definitely great to grasp underlying concepts in digital logic and discrete mathematics. However I do not need to know all that to be a successful programmer. Similarly with data science how much theoretical stats do you need to know to implement and extract coefficients from an sklearn logit model. One of my stats professor consistently argued that you could never average ordinal values, Which in practicality is not always the case and sometimes the best way to truly understand your data.

Only reason I weigh a stat degree over a data science degree is if you already have a technical background(comp sci or something). Reason being because today we have sklearn, tensorflow all those libraries. Tomorrow will bring new tech and new ways of validation via programming. I do believe with a stat degree you could always pick up the tools necessary to do stat more easily versus a technical person who was used to sklearn and now that it’s outdated has to learn new libraries to do statistics/ data science.