Data scientist/ml engineer interveiws
How are most of the data scientist or mle interviews at faangmula/big tech/unicorns like? Is it leetcode cosing style or SQL or ml algos or stats or python based questions?
Hiring managers are usually engineering managers when it comes to prod company, or some random outdated tech guy in some other companies. When you discuss collaboration, vision, ways of working with them in your interview etc. what challenges have you faced? What kind of disconnects do you think exists?
Very good point.. in my experience too I feel they try to focus on accuracy more and less value on business impact. They think that getting every model to give a more precise result is just to feed it more data and then any model can give 95+ accuracy but actually it depends on the problem statement and data we are having.
My point was maturity of senior leadership in building AI solutions is quite critical, if it's not there that would be one big challenge for an org to tackle. But the interviewer took it as I was speaking ill of my counter parts
How are most of the data scientist or mle interviews at faangmula/big tech/unicorns like? Is it leetcode cosing style or SQL or ml algos or stats or python based questions?
I was wondering what are some good questions to ask the interviewer at the end of the interview? They always end up with -"Do you have some questions for me?". To which I often ask the following -
What do interviewers usually look for in such interviews? What kinds of questions can we expect? I know its not purely technical but looking for some insights from those who would have gone through the same.