I could talk about a lot of specific circumstances, but in the interest of brevity I'll say this: The reason I believe a well-rounded statistics education is so

I could talk about a lot of specific circumstances, but in the interest of brevity I'll say this: The reason I believe a well-rounded statistics education is so valuable is because it ultimately teaches you to think critically about questions and answers. Good experimental design is driven by a solid understanding of theory--what statistical assumptions must be satisfied, which ones can be reasonably assumed or violated, and whether they're realistic to achieve. I don't believe you need a PhD to call yourself a scientist, but I do think one common trait most scientists share is curiosity. To that end, I would encourage practicing data scientists who might not have a formal statistics education to not shy away from statistical theory. A solid theoretical understanding is what guides you when the questions and answers aren't clear--and I think the fundamental shortcoming of many data science programs is that they prepare their students for extremely simplified (and therefore unrealistic) questions with easily obtainable answers relative to what will be encountered in the real world. I apologize for giving you an answer that isn't as coherent as I would like to it be. I tried not to be too verbose, but I think I failed at that anyway. I have a lot of feelings on this topic that I haven't fully articulated to myself yet. I could answer your first question if you're still interested, but as an addendum to my original comment, even though my statistics degree has gained me nothing in terms of career advancement or an increase in salaries or opportunities, its been truly invaluable to me as a programmer and a public speaker and advocate for the critical thinking skills it taught me. I hope others continue to recognize statistics value in academia and are curious of it.