Architect and scale robust table structures and analytics using expert-level SQL and Python to serve as the foundation for global risk detection and real-time reporting
Job Summary
Architect and scale robust table structures and analytics using expert-level SQL and Python to serve as the foundation for global risk detection and real-time reporting.
Design sophisticated fraud decisioning strategies by synthesizing login, entity, and tokenization signals to neutralize complex threats like Account Takeover (ATO) and high-risk transactions.
Optimize detection precision through rigorous statistical analysis, specifically leveraging False Positive Rate (FPR) modeling to protect the "Golden Path" of the customer experience.
Matching Summary
Architect and scale robust table structures and analytics using expert-level SQL and Python to serve as the foundation for global risk detection and real-time reporting.
Skills & Requirements
Must-have
Debit card fraud transaction strategies
Account takeover fraud strategies
Expert-level SQL and Python
Statistical analysis and FPR modeling
Debit card transactions and authentication frameworks
Nice-to-have
Forward-thinking company culture
Transforming financial services
Balancing security and user friction
Key Requirements
5+ years of work experience in Fraud Analytics
BA/BS in Statistics, Information Systems, Mathematics, Data Science, or related fields, or equivalent work experience