Lead Modeler (CAT Modeling, IED)
Risk Management Solutions - Newark, CA

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RMS is the world's leading provider of analytics and decision science solutions for the quantification and management of catastrophic risks throughout the world. RMS models and services are used by hundreds of insurance and reinsurance companies, hedge funds, corporations, and governments to assess a wide-range of natural and man-made perils, from earthquakes and hurricanes to terrorism and disease pandemic.

We are currently seeking a Lead / Principal Catastrophe Exposure Modeler to join our Exposure and Data Analytics Development team in the Model Development group. The Exposure and Data Analytics team primarily focuses on developing data products related to insured property exposures and industry loss curves. Such products are an important part of RMS product line and provide a wealth of valuable information for our clients.

The candidate will be working in a multidisciplinary environment with other catastrophe risk modelers across different time zones (California, London and India) and would be engaged in leading the development, design and implementation of a wide range of data models including data models used in catastrophe risk modeling, exposure modeling, property information modeling, casualty and human-exposure modeling, claim data and valuation modeling.

Essential Job Functions
In this role you will be primarily responsible for
  • Lead research and development activities related to property and casualty exposure modeling.
  • Research and mine socio-economic and engineering information related to insured properties mainly in American (North, Central and South,) European or Asian (East and Pacific) Countries.
  • Evaluating the Insurance policy language in P&C industry in such countries and translating those details to implementable assumptions.
  • Research insurance penetration in different countries and different lines of business.
  • Evaluating and implementing home-grown methodologies and solutions for property valuation.
  • Developing statistical models to estimate insured exposure using building permit data, census data, tax and other public data and etc.
  • Developing insured value estimates, localized deductibles and limits at different geographic resolutions such as postal code, county, prefecture, CRESTA, district, state and other geographic and administrative boundaries.
  • Executing analytics on exposure data provided by RMS clients, benchmarking RMS data products against such data and providing statistical regressions.
  • Data implementation of RMS products: SQL implementation of exposure data and QA of corresponding exposure products.
  • Producing loss and exposure maps across different countries and regions.
  • Loss trending, exposure disaggregation, historical event reconstruction/calibration and model projection (future trending).
  • M.S. or Ph.D. in an engineering or science related field including but not limited to: Civil and Structural Engineering, Financial Engineering, Operations Research, Industrial Engineering, Applied Math, Urban Planning, Econometrics, Actuarial, Science, Statistics or other related fields.
  • 5-7 years of experience in developing exposure models, catastrophe models or other relevant experience in predictive analytics.
  • Excellent knowledge of building systems, building design and construction practices.
  • Knowledge of engineering economy, building or project valuation methods and cost estimation is required for success in this position.
  • Understanding of risk modeling, risk assessment, uncertainty analysis in stochastic systems is required. Previous work experience or relevant courses to the subject is required.
  • Knowledge of probability and statistics is a must for success in this position.
  • High level of proficiency in data analysis, data mining and data manipulation software tools in particular SQL.
  • Excellent knowledge of a GIS software such as Esri's Arc GIS is required.
  • Hands on experience and knowledge of any of the following will be helpful: FORTRAN, C, C++, MATLAB, Visual Basic, or other statistical packages such as R, S-plus or SAS.
  • Detail oriented ability to learn quickly, strong analytical organizational skills.
  • A team player with a high-degree of self-motivation.
  • Highly organized and capable of managing projects.
  • Excellent written and verbal skills, as evidenced by technical presentations at meetings and conferences.

Risk Management Solutions - 22 months ago - save job
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Transforming the insurance industry's understanding and quantification of risk. RMS delivers the world's leading catastrophe risk models in...