Underwriter analyst RMS

Starr Insurance Companies is a leading insurance and investment organization, providing commercial property and casualty insurance, including travel and accident coverage, to almost every imaginable business and industry in virtually every part of the world. Cornelius Vander Starr established his first insurance company in Shanghai, China in 1919. Today, we are one of the world's fastest growing insurance organizations, capable of writing in 128 countries on 6 continents. This technically-oriented job focuses on two aspects of CAT Management: 1) Working with underwriters in the Technical Property and General Property units to determine account-level exposure to Windstorm, Earthquake and other natural perils, and 2) Compiling company-wide CAT hazard data in order to determine corporate-level C AT exposure. The primary tool for both functions is the RMS Natural Catastrophe Modeling suite of tools. Duties and Responsibilities 1. Auditing policy data to ensure proper entry in RMS 2. Populating and running RMS models for various CAT perils 3. Working with users in Starr branch office to assist with questions and problems with modelling Qualifications Excellent familiarity with basic computer applications especially MS Excel. Familiarity with the RMS model is a plus but is not essential as training will be provided. Knowledge of basic insurance terminology and policy/coverage language is also a plus but not mandatory, as is familiarity/basic proficiency with SQL. Starr is an equal opportunity employer, which means we'll consider all suitably qualified applicants regardless of gender identity or expression, ethnic origin, nationality, religion or beliefs, age, sexual orientation, disability status or any other protected characteristic. We recruit and develop our people based on merit and we're committed to creating an inclusive environment for all employees. We offer first class training and development opportunities to all employees. Our aim is to grow our own talent and bring out the best in people.

Created: 2024-11-12