fraudulent accounts based on transaction data, restricting transactions in advance to prevent harm. Responsibilities/Achievements: Development and deployment of credit card and financial features. Managing the data flow process from receiving variables to model predictions, identifying risk factors, and updating alert lists. Implemented Autoencoder + contrastive learning to achieve a 1.81% improvement in model effectiveness. Coupon Recommendation Objective: Personalized coupon recommendations for mobile banking users to increase click-through rates and redemption rates. Responsibilities/Achievements: Utilized multi-task learning to simultaneously predict click-through behavior and coupon redemptions, resulting in a
Python
R
MSSQL
Employed
Full-time / Interested in working remotely
4-6 years
政治大學
・
統計
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