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To someone unfamiliar with machine learning, how would you explain overfitting and underfitting? How do these concepts shape the development of models?

Can you define multicollinearity and provide an example of how it can impact regression analysis results?

Can you explain your approach to tailoring your findings for different audiences?

Which 3 personality traits do you think make you a success? In what ways do they align with Stitch Fix?

Have you ever received feedback that was difficult to hear? Can you share that experience?

Can you share a time when you had to explain a complex engineering concept to a non-technical team member and how you did it?

What’s your method for getting the product team to focus on the biggest customer pain points?

Create an on-demand food ordering system similar to DoorDash.

Assume you are an Amazon engineer. The review scores of Amazon items are sometimes biased, because people usually give a score only if they strongly like it or strongly dislike it. How would you know if the review score of a given item is biased or not?

In what ways is R-square an incomplete metric for linear regression analysis? How do you justify a low R-square value in terms of linear regression model fit?