Analyst, Data Science, Earnix Design
Design best-in-class capabilities to support post-modeling activities, including calibration, dislocation, and filing. Build USDS pricing programs in Earnix. Design and implement other use cases of Earnix as a rating engine. Ensure accuracy of all pricing and non-pricing outputs from Earnix. Design and maintain rigorous data models for Earnix analytical projects and API. As required, troubleshoot and support post launch queries and issues. Improve and automate processes where applicable. Engage with the data science community and participates in cross-functional working groups. Working familiarity with GLMs and GBMs for predictive modeling. Love insurance rating programs and want to get a deeper understanding of how they work. Frequently bring voices together to find patterns in business problems. Are comfortable challenging the status quo to make systems simpler, more robust, and scalable. Enjoy documenting and sharing best practices to accelerate the whole team. Get excited by delivering business critical, production-ready products. Experience creating rating logic and implementing rating programs in tools like Earnix, Radar Live, etc. Solid knowledge of predictive analytics techniques and statistical diagnostics of models. Foundational/intermediate knowledge of predictive toolset; expert resource for tool development. Demonstrated ability to exchange ideas and convey complex information clearly and concisely. Has a value-driven perspective with regard to understanding of work context and impact. Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and no professional experience, a Master`s degree (scientific field of study) and 2 to 3 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and 4+ years of relevant experience.