- Directs and leads department decisions and actions with respect to the following:
- Serves as a resource for best practices/quality on functional teams or projects. Works independently, with guidance in only the most complex situations.
- Trains, guides, and mentors other professionals or colleagues with less experience. Determines methods and procedures on new assignments and may coordinate activities of other personnel.
- Maintains current market knowledge and awareness of key industry trends in pricing/product segmentation and predictive modeling through primary and secondary research and attendance at analytical and industry
- Researches, develops and helps implement innovative pricing models based upon sophisticated predictive modeling/multivariate analysis.
- Directs adoption of predictive modeling methods to study client retention and conversion of quotes to new business issued; uses results to influence rating, underwriting and sales decisions.
- Develops companywide rating plans and recommended rating factors, based upon predictive modeling and data mining techniques.
- Produces segmentation models for P/C loss costs or retention.
- Performs highly analytical ad hoc projects especially as they relate to actuarial segmentation (territory, credit, underwriting scoring, evaluation of 3rd party vendor data).
- Networks on project implementation with key contacts IT, underwriting, actuarial, external vendor, or others.
- Bachelor’s degree with a strong emphasis on actuarial science, mathematics, finance or otherquantitative field (or the equivalent in related work experience).
- Eight years of Property/Casualty Insurance experience (or 6 years with an advanced degree), including five years in a pricing, product management or predictive analytics capacity (or the equivalent) and at least one year in a lead role.
- In-depth knowledge of Property/Casualty ratemaking theories, principles, and practices.
- Proven communication, interpersonal and collaboration skills to work effectively with various and diverse internal personnel and external contacts.
- Proficiency in multiple tools and techniques typically employed in predictive analytics (see supplement)
- Advanced degree (MS or PhD) in quantitative field such as mathematics, statistics, or econometrics, or data science.
- Experience working in SAS, R, EMBLEM.
- Experienced in multi-departmental projects.
- Demonstrated ability to manage periods of high pressure and shifting priorities to develop rates, perform studies, make recommendations and implement projects on short notice
- Work may extend beyond normal business hours as business needs dictate.