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Lead Data Scientist Interview Questions
347 lead data scientist interview questions shared by candidates
Two first-round technical data science interviews for two different roles within CVS Health. Both interviewers were very nice to speak with; however, their approach—and consequently, my impression—was completely different. 1. SQL Interview (should have been easy, right?) – Terrible experience! Three or four well-defined tasks were given. However, the partially written SQL queries and the lack of direction on whether I was required to modify the existing code or implement my own solution left me scrambling to debug the poorly written queries before even proceeding, as the original queries failed to run from the start. Oh, and the interviewer simply dropped the code into CoderPad, went on mute, and seemingly did other things, making it impossible to ask questions. 2. Python Interview – Excellent experience with the interviewer(kind & professional). The question was moderately challenging (LeetCode medium or a simplified hard), and although I wasn’t able to fully complete the solution in time, I was given a helpful hint along the way.
Typical behavioral and deep dive in technical projects with questions focused on ML design.
Technical test was a live, timed test where you could use any resources you needed to. It involved a series of short, straightforward Python tasks involving lists/dictionaries followed by a pandas data transformation task in a Google Colab notebook. Then I was asked to analyze a regression task output and any potential issues, followed by some general questions like, what are the pros/cons of random forests vs. gradient boosted forests; if you were trying to predict XYZ, what would you consider using, etc. Most of the other questions were around my past work or other case type questions - how would you solve this or go about doing this?
asked about projects, frameworks used , how you manage team, casestudy without data
They will ask you to solve a assignment - a binary classification problem
Explain how do you design a ML system for information extraction from documents?
Regression and what features to choose for regressions.
Tell about your previous project
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