Design, develop, and maintain predictive models, algorithms, and analytical solutions supporting pricing, underwriting, claims, and other P&C insurance functions • Apply advanced analytics and machine learning techniques to identify trends, risks, and business opportunities • Translate business and strategic objectives into clear analytics, reporting, and data requirements • Analyze large, complex datasets (structured and unstructured) using SQL, Python, Spark, or similar tools • Document, present, and explain modeling methodologies and results for business partners and regulatory review • Identify, evaluate, and integrate internal and external data sources to meet business needs • Collaborate with cross-functional teams to deliver practical, production-ready analytical solutions • Promote analytics best practices and provide consultation on data-driven initiatives • Evaluate third-party data, models, and analytical tools in partnership with vendors. 6+ years of advanced analytics, data science, or predictive modeling experience 3+ years of Property & Casualty insurance experience (strongly preferred in commercial P&C pricing, rating, or risk-tiering models) Strong knowledge of P&C insurance data, data sources, and business processes Proficiency in Python, R, SAS, or similar statistical programming languages (experience with at least two preferred) Experience working with large datasets using SQL, Spark, or cloud-based data platforms Familiarity with MLOps and machine learning platforms such as Databricks, Snowflake, Dataiku, or similar Strong written and verbal communication skills with the ability to explain complex analytics to business audiences Self-motivated, analytical, and collaborative mindset.