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Data Scientist

• Take ownership of model development, selection, and optimization with a focus on fraud and risk
• Oversee, maintain, and evolve in-house models using machine learning techniques
• Strong product bias with significant client-facing component to maximize product performance
• Model Development, Management & Evolution: monitor performance, identify improvements, implement enhancements with advanced ML algorithms
• Fraud Prevention: lead evolution of core fraud prevention capabilities, conduct build vs. buy analyses, assess third-party fraud models
• Model Governance: ensure models are governed, respond to model validation requests, explain functionality, provide performance and compliance evidence
• Policy Optimizer Analysis: leverage statistical methods to help clients configure credit policies and optimize underwriting rules
• Customer Success: work with customers to evolve and maximize credit and fraud policies via regular meetings and insights
• Cross-Functional Collaboration: partner with Product, Engineering, and Customer Success to integrate and optimize models
• Data-Driven Insights: analyze large datasets to uncover trends, identify risks, and find opportunities for product innovation

Director of Fraud, Risk, and Data Science