explain about your projects. metrics used.
Principal Data Scientist Interview Questions
156 principal data scientist interview questions shared by candidates
Fairly standard tech interview, a bit light on the coding side.
Mostly technical questions pertaining to my past experience including A/B testing and approaches implemented to perform validation of ML models.
They give use cases and later on questions regarding it, similar to traditional McKinsey, but with a more technical focus.
Q: What is the your weakest and strongest part?
Q: compare two analysis methods
A discussion about problems they face and solutions and general discussion about LLMs and deep learning
What's an example of a time that I received critical feedback?
how do you ensure a good estimate of the probabilistic distribution after predicting a binary variable? what metrics would you use to evaluate the probability estimate of a model? why wouldn’t random grid hyperparameter tuning not work and what would you use instead?
What’s an interesting technology or technique you’ve been learning about? Tell me about a design decision you made that you weren't weren’t happy with. What are some exciting technologies?
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