Parsing realistic (messy) JSON, usually. I would have expected F# to shine at that due to type providers, so it was doubly surprising to me. The F# candidates I've seen spend most of the interview manipulating the data.
It's unfortunate that they decided to pick F# on such problems when they didn't have the (mental) toolkit to tackle them, but I think it speaks more to people being really eager to communicate their enthusiasm for FP. I wouldn't try to ascribe any higher meaning to it.
However technical capability and efficiency of the tool isn't the only concern picking up the comments in this thread so far. The herd effect sadly can make people nervous creating a barrier for people to try it especially if career is in it. What other people think of it, and their preconceived notion can matter.
But tbh, from what little I know, I'd be expecting you to expect me to solve the issue from first principles. So using a "and then magic" technique might be something interviewees shy from.
Normally now I ask Chat GPT to create an F# record from the JSON. Then go through and check everything line by line, redo the types to something sane and use that.
But if it were a quick script to do a one off then a type provider will work well.
Depends on what you mean by messy? Non-conforming JSON? A custom FParsec parser might be able to sensibly extract the data. If it is conforming to JSON then you'd use normal F# code to work with the standard JSON parsers.