Questions like this one are both shallow and pointless, on many levels. It is like asking what kind of classical guitar is it best to use for playing scales. Obviously, if you want to practice scales, it doesn’t matter what kind of guitar you use. You play the scales for improving your technique. As for playing a musical piece, if you are a good guitarist, you can play that piece well, even with a cheap guitar.
Of course, the matter of the OS is more polarizing than a guitar, which is why people have a hard time seeing the merit of another OS. Also, for many people the OS they use is part of their identity, much like people who support a particular sports team in such a way that they are willing to get violent towards the supporters of another team. The difference in this case is that the violence is over the internet usually and takes the form of passive-aggressive comments and insults.
Data science is a field of science, focusing mainly on applications. As a result, a data science professional is more concerned about the way she works with the data at hand, to make it into something useful. More often than not, this involves some predictive analytics model too, which she has to train, test, and fine-tune. All that stuff she does without any concern about the OS used, since the programming language she works with is cross-platform. Also, if she is able to work that programming language well, she won’t have issue with shell scripting in a particular OS, which is fairly simple by comparison.
Now, some OSes are faster than others, so someone may prefer that, even if it usually comes at a cost. The latter involves the lack of user-friendliness that a faster OS usually has. Whatever the case, if the code created is done well, it’s bound to be fast even in a slower OS. Also, if the code needs to run for a long time, then it’s probably better off being run on a computer cluster or on the cloud, so the OS you use on your computer is not that important.
So, if you are comfortable with OS X and can do your data science work there efficiently, that’s all that matters. Let the people who have nothing else to do argue about which OS is better or worse for data science. If those people weren't arguing about this trivial matter, they’d probably be arguing about which soft drink is better, or which sports team should win the championship. As a data scientist you have better things to do than waste time talking with them, since it’s unlikely they are going to ever change their minds about their view anyway.
Zacharias Voulgaris, PhD
Passionate data scientist with a foxy flair when it comes to technology, technique, and tests.