高频题（0）
1. Python Data Manipulation Using Pandas
The interview involves a data manipulation task using Pandas in a Jupyter notebook shared by the interviewer. The data set is about transactions with a primary key of movement_id, and includes fields like timestamp, amount, and category (such as P2P). The task is to calculate the Year-over-Year (YoY) change for each category and interpret the results. Skills tested include using joins, lambda functions, and string manipulation in Pandas.
2. Cash Back Calculation
Define a function to calculate cash back based on certain conditions provided to you.
3. Year Over Year Growth Calculation
Using the transaction table, calculate the year over year growth.
4. Calculate Profit by Category
Given a transaction table, calculate the profit for each category. You can choose to calculate either the sum or the average.
5. Machine Learning System Design for Churn Prediction
Design a machine learning system for churn prediction. Emphasize the model building aspect and the selection of appropriate metrics, rather than the deployment of the model.
