Actuary & Data Scientist

  • 36998
  • Non-Life - Actuarial
  • |
  • Florida, United States
  • |
  • Mar 11, 2020
Insurance
RESPONSIBILITIES
  • Supports actuarial and business intelligence needs for a diverse portfolio including Homeowners, Business owners, Builder’s Risk, Flood, and Surety.
  • Leads and develops predictive analytics/modeling efforts and use of associated analytics/modeling programs.
  • Prepares the predictive analytics and catastrophe modeling support needed for strategic pricing decisions including data collection and cleansing, market analysis and filing support needed for internal customers, external vendors, reinsurers, regulators, and rating agencies.
  • Performing complex statistical analyses to determine pricing and market segmentation opportunities for our product lines.
  • Assisting management with the development of procedures and standards regarding predictive modeling; identifying, collecting, verifying and preparing data for use in predictive and cat modeling; designing and constructing datasets to facilitate the modeling process, design and implement metrics to monitor model expectations against experience to determine areas of model weakness.
  • Analyzes profitability measures and works proactively with Product Management to maintain required rate adequacy through rate filings and other non-rate actions, such as new underwriting rules or risk selection criteria.
  • Interfacing with Corporate Actuarial reserving team, when appropriate especially at year end.
QUALIFICATIONS
  • Bachelor’s degree in mathematics, statistics, finance, economics, or related field.
  • Can be in a current actuarial or predictive analyst track of the Casualty Actuarial Society or have multivariate predictive modeling and /or cat modeling P&C experience.
  • The ideal candidate should have at least 3 years of insurance-related experience with emphasis in traditional actuarial roles, programming, or quantitative analysis.
  • Working knowledge of basic ratemaking and reserving techniques. Experience with catastrophe models, predictive modeling techniques and reinsurance is a plus.
  • Proficiency in programming languages, such as Microsoft Excel, SQL, SAS/JMP, Emblem, Python, R or similar software. Familiarity with cat modeling and analyzing RMS, AIR or similar outputs.
  • Ability to work independently and collaboratively to solve problems.
  • Execution-oriented with strong organization and project management skills.
  • Strong written & oral communication skills, including experience in Microsoft PowerPoint.