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What do you believe will be the biggest challenge in the GitHub Data Scientist role?

If you took an unpopular decision, please tell me about it

Share a story about a time when you didn't reach a goal.

Briefly describe your background and what is your most relevant experience within GitHub

Decision trees and bias and variance - could you give us insight into how they relate? And in particular, which of those two is more tricky to manage: high bias or high variance, and what's the explanation behind that?

Suppose you had the opportunity to change something at GitHub. What would you change?

Could you explain your methodology for determining the fees for riders to use our service?

If the labels are known in a clustering project, how would you evaluate the performance of the model?

How would you describe your biggest accomplishment so far.

Is it possible for you to create a KNN classifier without relying on external resources?