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Can you elaborate on your decision-making process for handling datasets that display class imbalance issues in binary classification?

Why are you looking for a job at the moment?

Write a function to find the problematic integer in an array of sorted integers from 0 to n. Your solution must have a time complexity of O(log n).

What is your recommended approach for normalizing a dataset with 50 behavioral variables and 500 contextual attributes in order to identify outliers using unsupervised learning? Moreover, how would you use evaluation metrics and visualizations to assess the performance of the model?

Tell me about a difficult conflict you managed.

Can you talk about probability distribution that breaks away from the standard normal distribution? Additionally, could you give an example of a field where this probability distribution is relevant?

As they apply to decision trees, how do you explain bias and variance? Also, which is harder to tackle: high bias or high variance, and what's the basis for that?

What would you like to gain from the position of Data Scientist at Chime - what are some of your key goals?

How are k-means and KNN distinct from each other in terms of their applications?

Given preorder and inorder traversal of a tree, construct the binary tree.