Wouldn't your approach be biased against people who need more time to come up with a solution, and against people who are not used to discussing their solutions

Wouldn't your approach be biased against people who need more time to come up with a solution, and against people who are not used to discussing their solutions with others in real time? You approach also doesn't include an objective measure of performance: Your judgement of the candidate could be highly dependent on their personality, instead of their actual skills. If I recall correctly the book "Thinking fast and slow" shows how easily interviewers are influenced by personality traits. Technical questions like "how do you invert a binary tree" or "what is KL-divergence" are much less personality dependent, and the quality of the answer is measurable. Here is what I think are some important skills in data science: Can you understand the principles behind existing solutions and build a new solution from those principles? (How fast) can you understand a new approach and apply it to a problem? How long does it take you to translate a solution to working code? How optimal, readable and reusable is it?