1. Brief Self-Introduction in All the Rounds. 2. Recruiter: What do you know about the business? Why are you interested in the role within the business? Projects/Qualifications/Skills overview relevant to the role. 3. Hiring Manager: Projects deep dive questions relevant to the role. 4. Team: Data Structures, OOPS, Ethics and Governance, Measuring Sucess, Goals, Code structure, and Key components, Python-type questions.
They asked about my previous experience in the field.
Ask about my availability every time only
2- deep learning, cnn, rnn and regular ML questions, regularization, SVM, bias variance trade off, batch normalization, PCA, PLS
STAR assessment and presentation on challenges in the area of interest
What is the difference between random forest and xgboost
First interview - Technical questions about the solution proposed (why random forests, difference between other algos, etc)
They don't know anything about ML and data science. They have already dissolved there data science team once because of incompetency.
Tell me about a time when you have had conflict of interest
Normal around resume ml stuff doesn't seem anything different
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