So if deriving log likelihood formula in high pressure, time limited situations, is a good proxy for the kind of work the candidate will be doing, by all means do it that way.
If on the other hand, they are more likely to be asked on the job, to go away for some time, think about the questions needing answers in a data set, design an algorithm to suss out those answers and then persuade their colleagues that it is correct, you should design your interview process to align with that.
We’ll ask you to solve some coding questions in a language and text editor of your choice. Feel free to bring your own laptop, or we’ll be happy to provide one. Notably, we ask candidates not to compile or run their code during this exercise, and not to refer to online resources. Our goal is not to simulate day-to-day software development — where we read docs and write lots of tests! — but rather to see how you reason about your code and input cases. For that same reason, we won’t ding you for superficial syntax errors or misremembered function names. After leaving you to work through the questions on your own, we’ll sit down together and talk through your solutions (including any ideas you didn’t have time to commit to code).
In any case, all I'm disputing is the idea that formal reasoning about algorithms (without stressing function names and compilation) is a useless skill. We have tools that make it unnecessary for many entry level devs, but that doesn't mean everyone can ignore it.
To me it sounds exactly like they want you to demonstrate some semi-formal reasoning about algorithms, and you think this is not a realistic representation of work. What do you think they mean, and what do you oppose?
As another example, I ask people to set up numerical/statistical algos without worrying about specific numpy details. I trust people to translate a log likelihood formula to python, but I want to see them actually derive that formula. This isn't some hazing ritual - it's important to actually understand the statistics to avoid getting stuff wrong.
Again, the tools won't help you - if you set things up wrong, you just get a bunch of false positives.
I understand this isn't very important for the average dev writing CRUD or ETL apps. I'm just pointing out a particular use case where their constraints are reasonable.