What direction or project you want to work on
Principal Data Scientist Interview Questions
163 principal data scientist interview questions shared by candidates
explain about your projects. metrics used.
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?
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