Position: Data Scientist
Outcome: Onsite Rejected
How was the interview process? What was it like?
I knew you had to code quickly and you have to keep it in mind. The code interviewer might not directly signal you to do it and it can waste time. There are very few behavioural questions. There is a very wide amount of stats questions to study for and you won't have time for derivations or talking about more advanced uses. I think it would be useful to have a 'cheat sheet' with a summary of what's on brilliant as well as some distribution figures for sample events i.e prob ad click or hours spent per day.
What technical questions were asked?
Probability, SQL / Pandas, Business Case and Estimation, Product Metrics and Measurement
What was one of your solutions?
I described most above, for the applied data I made an answer based on their ad allocation system. Match a bucket of users to a bucket of restaurants. This is a good talk https://www.youtube.com/watch?v=94s0yYECeR8
For the product one I mentioned island tests but the interviewer wasn't clear on what they were looking for. Apparently they wanted to talk about network effects but I did mention that. Hinted towards doing a test in New Zealand vs Australia - how do you make that fair. Again, not very clear.