My experience: 0 years, 2 - 3 internships during my Ph.D. though

Phone round 1:

Q1 - https://leetcode.com/problems/add-two-numbers/
Q2 - https://leetcode.com/problems/interleaving-string/ (It was a much simplified version of this. Instead of 3, given two strings check if target can be generated using them, not necessarily interleave)

s1 = 'bloom', s2 ='berg', target='bloomberg'
ans = True

s1 = 'bloom', s2 ='berg', target='bloomberg1'
ans = False

s1 = 'blom', s2 ='oberg', target='bloomberg'
ans = True

Phone round 2:

• What is L1 and L2 norm?
• What is the difference between SVM and Logistic regression, why SVM?
• What is overfitting and underfitting a model? How to identify and correct it?

After these warm ups, he asked ML system design question:

• Design a spam email detection system. What if instead you were to identify spam tweets?

The second interviewer wasn't convinced with my ML system design at all. We both hated each other by the time it ended. I asked him, how will generally Bloomberg evaluate me AI scientist role since it is not just coding. His answer 'Based on the questions we ask you in the interview' :excuse me?: