What is bias/variance tradeoff? What are some regularization techniques? Explain each one. What are some techniques to assess goodness of fit?
Sr Data Scientist Interview Questions
3,505 sr data scientist interview questions shared by candidates
How do you troubleshoot if something is wrong in production?
The getting-to-know-you chitchat that's average fare for initial recruiter calls.
Questions about one of my projects
In the second half of the interview, I was asked to design a recommendation system for confluence, to recommend articles. NOTE: They say that they ask system design question according to the resume or our previous experience, but I havent worked on a recommendation system previously. So it might be a question based on the teams requirement. The interviewer mentioned that he has experience working on recommendation and it is his field of expertise.
Measure the success of [[insert Slack feature here]] using this dataset. Trust nothing.
Coding exercises
experiments and key metric related q
- Diagram a solution for a multi-modal document prediction task. - Explain overfitting in the context of various algorithms (SVM, random forest, neural network) and techniques to mitigate it (very technical on the details) - Explain how you would deal with class imbalance or other sources of bias in a training data set (again, very technical on the details) - Explain how you would use a Docker container to make a deployable machine learning service using Kubernetes (wanted many devops details). - Have you used a pipeline automation tool like Luigi? Have you used monitoring tools like PagerDuty?
schema based SQL questions purely depends upon your understanding.
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