In the technical round, they asked questions on the basic of Machine Learning followed by few case studies on the real-time project they are doing. In HR round, they asked all common HR questions like why you wanna join the company, why you are living your current job etc.
Tell me about your experience in credit modeling?
Describe how do you use CNN as your project? How difficult it is to explain the feature importance in deep neural networks.
Your data science experience and previous projects
"You are using a performance matrix to see how well a model performs. Describe the matrix."
"How would you identify outliers?"
"How would you address imbalanced data?"
"How can you ensure that a model does not have multi-collinearity?"
"What criteria would you use to determine how reliable the control and test group are?" (follow-up to question #5)
How much data is enough to build a machine learning model? What actions can be taken using the machine learning model you created?
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