Data Scientist II

Develop, validate, and optimize internal fraud and authentication models to reduce reliance on external vendors. This hands-on role involves end-to-end model development, from data discovery to production support, and requires collaboration with various teams to translate business challenges into analytical solutions.

• Develop and optimize machine learning models for fraud detection and authentication
• Lead end-to-end model development lifecycle
• Evaluate internal models against vendor models using fraud and risk metrics
• Build reproducible workflows using Python, SQL, and enterprise data platforms
• Perform model monitoring, diagnostics, and issue investigation
• Prepare documentation and present results to technical and non-technical stakeholders