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Do you have an example of when you disagreed with another team member's approach?

Can you explain to me why you think StubHub is the right fit?

In cases where one class is much more prevalent than the other in binary classification, what measures do you put in place to overcome this imbalance?

How would you employ an algorithm to separate fake from legitimate news, and can you implement it for us?

In a machine learning problem, if you have a high-dimensional dataset, how would you go about handling it?

Which is faster, joins or subqueries?

Could you tell us why you'd make a good fit for StubHub?

If metrics suggest low user engagement in the lead-up to a new product launch, what steps would you recommend to the product team?

If you receive an offer from StubHub, how long do you think you'll stay here?

For those of us not well-versed in decision trees, could you provide an explanation of bias and variance and how they're pertinent? Additionally, could you share with us which of those two is tougher to deal with: high bias or high variance - and why?