Develop, deploy, and monitor fraud detection models and pattern-recognition pipelines using Python, SQL, machine learning, and large transactional datasets. Partner with Fraud Operations to refine models, reduce false positives and negatives, analyze emerging fraud trends, and improve underwriting and verification strategies. Communicate insights to senior stakeholders, apply AI in production, and lead team members and initiatives.

Own value-based bidding across digital marketing channels by building customer lifetime value models, integrating predictions with Google Ads and Meta, designing incrementality experiments, and advising Marketing on budget allocation, audience strategy, campaign measurement, and funnel performance. The role requires production-oriented machine learning, statistical analysis, automated data integrations, and collaboration with Pricing and Profitability teams.

Lead development and independent validation of advanced credit risk models used for lending criteria and verification. Prepare validation reports, monitor model performance, support production releases, and improve validation methodologies through automation, data manipulation, machine learning, and programming. Provide technical guidance and mentorship while communicating quantitative findings to technical and business stakeholders.