If you’re set on the (data science, I presume) PhD, I would suggest a SE internship. The rationale is that you’re going to be deep in DS for a few years so this is a good opportunity to explore another field. And what you learn during the internship (how to write clean code and document it, unit tests, version control, seeing production software) will a) put you in good stead for your PhD which presumably will be code-intensive and b) set you apart from the rest of the data science pack once you graduate. I work with (junior / intern, to be fair) data scientists and OMG, bashing together a Jupyter notebook != knowing how to program. How to get from a trained model to production code is in my opinion a vastly underdeveloped topic in data science. Having SE experience will definitely help you see how the other half lives.