I'm currently a computational Statistics major at UC Davis and have my eyes set on becoming a data scientist. I like both fields of stats and computer science, but not sure if I want to put in the effort to double with computer science, since my only career goal is to become a Data Scientist. How important are the set of skills taught in comp science and not in statistics to Data Scientists? Is it worth the double major effort?
If becoming a Data Scientist is your only ambition, I doubt you require to complete an entire major on computer science.
In a computer science major you will learn a lot more ranging from programming languages, semantics of both software and hardware design, data structure, computer architecture and organization, signal processing, AI among many others. Most of which is not even directly connected to data science. In fact a standard computer science graduation course that I've been through (both my undergraduate and graduate) did not have any element of data science in it -- no data mining, machine learning or inferential statistics. Well, most of these subjects are included as part of the current generation syllabus. But the main point is that you would learn a whole lot more than what is needed to become a data scientist if you were to take a computer science major.
Computational statistics encompasses a major part of data science, one that a computer science major would cover is lesser proportions. I suppose you would cover a considerable portion of data science just by following your current major. I've resorted to online courses and practising the skills myself to learn data science. I find this more helpful. Also, bear in mind that not all successful data scientists are computer scientists.