Campus Graduate Masters Full-Time Manager Onboarding - 2027 Global Decision Science, Credit & Fraud Risk - New York, NY

Business Unit/Role Specific Information

The Credit and Fraud Risk (CFR) team at American Express employs 3,500 global professionals focused on managing credit, fraud, and banking risk, optimizing risk trade-offs while delivering exceptional customer experiences. CFR’s work spans the entire customer lifecycle, supporting core processes like credit underwriting, fraud detection, servicing, and product development while also maintaining regulatory compliance and operational integrity. CFR leverages advanced analytics, data science, and AI/ML techniques to drive risk modeling, personalize decisions, and enhance customer experiences.

As a Data Science Manager, you will support the development of predictive models used across credit, fraud, and marketing to inform key business decisions. They apply statistical techniques and machine learning to real-world datasets, contributing to innovation in areas like customer personalization, risk management, and regulatory compliance.

How will you make an impact in this role?

- Query and manipulate large datasets using tools like SQL, Hive, and Python.

- Build and test predictive models using machine learning techniques (e.g., logistic regression, decision trees, clustering).

- Document modeling choices and provides rationale for algorithm selection.

- Translate business goals into technical requirements and analytical questions.

- Develop a clear and structured final presentation that communicates the project’s purpose, methods, insights, and business impact.

- Analyze current decisioning models, develop and implement a plan to improve model prediction accuracy.

- Improve automation of customer connects via a GenAI enabled chatbot tool.

- Use deep learning to uncover hidden trends in fraud and credit bust-out.

- Programming (Python or R) – Writing scripts for data analysis, modeling, and automation.

Minimum Qualifications:

- Master's Degree

- Candidate with 3+ years of relevant professional experience

- Effective team player with interpersonal skills; capable of working autonomously or collaboratively in cross-functional teams.