Job Interview Experience For The Role Of Data Scientist at Capital One
1. How would you build a model to predict credit card fraud?
2. How do you handle missing or bad data?
3. How would you derive new features from features that already exist?
4. If you’re attempting to predict a customer’s gender, and you only have 100 data points, what problems could arise?
5. Suppose you were given two years of transaction history. What features would you use to predict credit risk?
6. Design an AI program for Tic-tac-toe
7. Explain overfitting and what steps you can take to prevent it.
8. Why does SVM need to maximize the margin between support vectors?
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