Questions were mostly on your data challenge, hypothesis testing (how you would set something up, etc) and Bayesian stat (how you set up a prior, etc). Again tech questions are not hard and they kept asking about if I would be comfortable working with customers or non-tech people.
Machine learning algorithms
1. How many DS projects worked till date. 2. What is confusion matrix. 3. What is correlation. 4. Have you worked in marketing/sales?
Fundamentals that a qualified data scientist should know
Given a fair and unfair coin, calculate the probability that if heads comes up 5 times in a row, you have the fair coin.
Take home: Setup ML pipeline question.
What are your strengths/weaknesses? Tell me about some of your projects.
Tell me about a time... Describe in detail your last 3 production deliverables, what the problem was, how you approached it and what you did to solve it.
How I would approach classifying a disease using EMRs?
Basic EDA, Behavioral questions on previous experience
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