Lead and scale a production-focused data science practice: define engineering standards, build reusable Python frameworks, drive end-to-end model development and monitoring, collaborate with Data Engineering/MLOps/analytics and business partners, mentor team members, and establish measurement, documentation, and prioritization disciplines to ensure models deliver business impact across Claims, Underwriting, Risk, and Distribution.

Build and maintain an in-house insurance rating engine using Python. Collaborate with stakeholders to gather requirements, design features, implement back-end and front-end components, analyze customer data for rating accuracy, debug data issues, and apply P&C insurance concepts to technical solutions.