It's a bit of both. You are unlikely to ever achieve a position in industry that has the same freedom of investigation and time that you experienced as a gradu

It's a bit of both. You are unlikely to ever achieve a position in industry that has the same freedom of investigation and time that you experienced as a graduate student, let alone the holy grail of a self-funded post-doc or the like. On the other hand, you won't achieve that as faculty either. In industry you're going to end up spending a lot of time on activities and meetings that don't relate to what you now consider "what you do" (e.g. ETL, domain interview, co-ordination etc.). Your success and happiness in this will depend a lot on whether you consider those things a waste of time taking you away from what you "really do", or an important part of how you do such activities in larger groups. On the other hand, data science has a similar problem as software programming; failing to know how to find or produce good managers for it, companies tend to promote from the ranks of their best individual contributors. This can work well with enough support and mentorship (assuming the candidate wants to do it) but it can be a disaster without a plan and that support.