HR interview was easy but second interview with manager was mainly about previous experiences and highly difficult. So, studying on or remembering the projects would be really helpful. I wasn't remembering any single detail that's why it didn't go really well. Deep questions like dataset size and balanced/ imbalanced data, resulting training and testing accurancy, theoretical machine learning algorithms are asked. The manager was really professional and expert on data science though.
Tell me about a project where a client was not happy.
What is xgboost? what are hyperparameters that we use in xgboost.
asked me about the various accuracy metrics in detail
Given this UX flow from lead to sign-up for a monthly subscription, how would you aid product managers in testing improvements to the flow to increase subscriptions?
Tell me about a time when you've had to juggle a lot
Tell me about a project you're most proud of and why?
Q. How did you communicate the project results to stakeholders
Did you do any statistical modeling?
How to prevent overfitting in a ML model?
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