They are really reasonable about questions. Just explain clearly what you have done before, the questions that they have a open ended discussions. If you can talk on a subject matter and give a few angles on a problem that is all they are looking for.
Which part of our product you dislike most? Then can you think of the reasons why we decided to make it that way? And how would you quantify its badness (goodness)? How would you fix it? And why it will fix it?
What is the difference between a data scientist and a data analyst?
Data Science Questions based on the case study you present
Difference between boosting and bagging?
How to tackle a long term forecasting with ML approach? (direct, recursive, hybrid...timeframe training like weekly or daily basis)
How would you improve the way of working of different teams which team would you like to join and why
Walk through projects and explain
describe random forest algorithm
The recruiter just asked some high-level questions about my past experience, and insisted that they were handing out take-home assignments to everyone when clearly it was false.
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