That's why FAANG still do whiteboard/algorithm questions.
If implemented properly you get a good idea of who can code and solve problems, and who can't. Of course, there are false positive and false negatives, but the signal to noise ratio is pretty good.
> If implemented properly you get a good idea of who can code and solve problems, and who can't. Of course, there are false positive and false negatives, but the signal to noise ratio is pretty good.
I see the idea, and I try to focus interviews on 'show, don't tell', but is there research supporting better outcomes?
Sadly it's all empirical.
Do you trust HR or the hiring team more to filter candidates?
It's a valid question. Keyword / minimums tilt the balance in HR's direction. Whiteboard / algorithm questions tilt towards hiring team.
I essentially hired one guy I interviewed because he seemed intelligent and did motorcycle work on his own. Had some background in the specific subject, but I'd rather hire a demonstrated ability to learn & initiative. (Afaict, he's thriving and a great fit for the position)
Me too, and I respond similarly to information like that. But the #1 hiring bias is hiring people like yourself. It's possibly I am just falling victim to that bias.
Keywords are almost always pointless. I've seen extraordinary resumes that ticked all the boxes, yet 20 minutes in there was not a working FizzBuzz on the door.