Kedarnath Pamarthi

Developed and optimized data-driven insurance rating algorithms used by major Canadian insurers (RBC, Canada Life, Desjardins, Blue Cross, Beneva). Worked with large actuarial and financial datasets, ensuring accuracy, consistency, and clean structure for downstream analytics and modeling. Built and maintained backend components using Java, SQL, Python, and proprietary DSLs to support enterprise insurance platforms. Collaborated with cross-functional teams to translate business rules, data requirements, and client specifications into reliable, production-ready systems. Performed detailed debugging, QA validation, and data verification to improve system accuracy and reduce calculation errors across products. Automated repetitive data tasks, improving efficiency in rate updates, data extraction, and validation workflows. Integrated complex data sources (experience data, rate history, eligibility data) into scalable pipelines used for rating and renewal calculations. Ensured clean, well-structured input/output data formats for external teams, analysts, and client-facing systems. Supported the creation and interpretation of actuarial logic, helping bridge the gap between business, data, and engineering. Provided technical guidance and issue resolution during client meetings and production deployments.