Tech Stack

Description

You will design, develop, and deploy fraud models across SoFi products, using machine learning to reduce fraud losses and false positives while collaborating cross-functionally to inform strategy and manage model risk.

Requirements

• 7+ years advanced quantitative modeling or equivalent (Master's +5, PhD +3)
• Production ML models with measurable fraud impact
• Deep expertise in Python, SQL, and data visualization
• Strong knowledge of statistical methods and ML techniques
• Experience collaborating cross-functionally with Risk, Ops, Engineering, etc.

Responsibilities

• Own end-to-end fraud model development from problem framing to production monitoring
• Drive measurable reductions in fraud loss, false positives, and operational expenses
• Translate model outputs into business impact metrics and influence fraud strategy
• Aggregate and synthesize datasets for scalable modeling frameworks
• Establish and maintain model monitoring standards (performance metrics, drift detection)