Senior Graph Data Scientist - Identity Analytics

This senior role develops and deploys quantitative solutions and graph-based systems to improve USAA’s ability to detect and prevent identity theft, account takeover, and first party/synthetic fraud. You will build machine learning models, implement Financial Crimes graph database strategies, and share modeling methodologies with the analytics community.

• Develop and continuously update internal identity theft and authentication models
• Deploy a Financial Crimes graph database strategy including vendor selection and use cases
• Use graph databases and graph techniques to identify criminal networks and fraud patterns
• Drive continuous innovation including advanced techniques like graph neural networks
• Integrate new data sources and export insights to decision systems for fraud targeting

The job centers on machine learning for identity theft and fraud detection combined with graph analytics and graph databases. You will deploy graph techniques and advanced methods such as graph neural networks, integrate new data sources, and export insights to decision systems to enable better fraud targeting and model development.

The ideal candidate is a senior data scientist with strong graph analytics and machine learning experience focused on identity theft and fraud prevention. They can develop and continuously update identity and authentication models, design quantitative solutions, and deploy graph database strategies to detect criminal networks and fraud patterns. They are experienced collaborating across fraud identity analytics and technology teams and leveraging advanced techniques such as graph neural networks.