Five people during "in-house": One algorithms/coding, breadth and depth ML (one each), one ML architecture (recommendation systems), one "leadership principles".
Senior Scientist Interview Questions
5,826 senior scientist interview questions shared by candidates
what is your name ? and did you speak to someone else in the company before?
Very specific to my previous experience on the category from design all up to scaling up and commercialization aspect.
Why is VIT better than Convnets?
Do SQL joins with out using Join?
Fundamentals such as difference between covariance and causation , Bayer Theorem. Questions about my previous projects Explain over fitting to a client
Questions around projects done in earlier workplace. Explanation of some core deep learning concepts and it's application. Discussion on details of model and data science application experienced during earlier projects.
Was shown a data graph and asked to interpret results
The technical screening involved some leetcode style problems and general problem solving + ML questions. The round table was a mix of behavioral questions, statistics, ML, and at least 1 more instance of leetcode problems. Question difficulties ranged from easy, like "how to address in the dataset", to average difficulty questions like "explain the differences between and another" or "can you describe how works.
A project you worked on, feature selection, over-fitting of the model. What do you do when the features are correlated. What is the main difference between the F1 score and ROC-AUC? How do you decide between different models? What does MLE correspond to in Logistic Regression?
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