Advanced degree (MS or PhD strongly preferred) in Economics, Statistics, Econometrics, Applied Mathematics, Computer Science, or a related quantitative field
10+ years of applied experience in data science, fraud analytics, risk research, or quantitative economics, with demonstrable impact at scale
Proven expertise in fraud, identity risk, financial crime, or adjacent domains
Strong command of causal inference, statistical modeling, and modern ML/AI techniques applied to adversarial or risk problems
Track record of external thought leadership — publications, conference presentations, regulatory engagement, or equivalent market-facing credibility
Exceptional written and verbal communication skills; ability to author compelling, rigorous, market-facing research
Experience leading and developing high-performing technical teams