Tech Stack

Description

In this role, you will develop and implement fraud prevention strategies for debit card and account takeover threats, leveraging SQL and Python to build scalable data systems. You'll collaborate with cross-functional teams to balance security with a smooth customer experience.

Requirements

• BA/BS in Statistics, Information Systems, Mathematics, Data Science, or equivalent experience
• 5+ years in Fraud Analytics
• Experience managing risk-decisioning for debit card fraud (ATO, 3DS, CNP, Tokenization)
• Deep mastery of trade-off between fraud mitigation and UX
• Expert-level SQL and Python skills for building automated data architectures

Responsibilities

• Architect and scale robust table structures and analytics using SQL and Python for global risk detection
• Design sophisticated fraud decisioning strategies to neutralize account takeover and high-risk transactions
• Lead cross-functional initiatives balancing security and user friction
• Optimize detection precision through False Positive Rate modeling
• Execute end-to-end risk-decisioning for debit card transactions and authentication frameworks