I used to interview people for data science roles. We let people use whatever language they wanted in the interview. I expected to see a split between Python and R, but the reality was that almost everyone used Python, which was a bit of a surprise.

It's even more surprising to me given that Pandas is such a poorly designed library. (Apparently the guy who developed it was learning Python while he was writing Pandas.) I saw candidates make mistakes due to quirks in Pandas often. And quirks can be extra deadly with data science code: https://news.ycombinator.com/item?id=33797339 So overall it's a weird situation. I think a big factor is that a lot of data scientists are newbie programmers who are just piling in to what's popular & established.