About the role

What you’ll do

• Lead fraud risk analytics and strategy across the customer lifecycle and store/online channels
• Balance fraud losses, approvals, customer experience, and operational cost
• Build, deploy, and monitor fraud models using machine learning techniques
• Partner with Credit Risk and other teams to detect and prevent fraud
• Manage and develop a high-performing fraud analytics team
• Ensure data quality, ELT, and feature engineering for fraud identification

What you’ll need

• Bachelor's degree in a quantitative field required; Master's or PhD preferred
• 5+ years in fraud analytics, fraud strategy, or risk data science, including 2+ years leading analysts; 8+ years and 4+ years of management for Senior Manager
• Advanced proficiency in SQL and Python or R
• Hands-on experience building, deploying, and monitoring fraud models using machine learning techniques
• Deep knowledge of consumer lending fraud typologies, controls, fraud data vendors, and decision engines
• Working knowledge of model risk management and regulatory expectations such as FCRA and ECOA

Original job description