Job Description

Overview Risk Management Solutions (RMS) is the world's leading provider of solutions for understanding the risks of natural catastrophes. Our Model Development group builds the models and data at the heart of these solutions, quantifying the potential impacts from earthquakes, tropical cyclones, floods, and other natural and man-made perils. Our clients include several hundred insurance and reinsurance companies as well as brokers, banks, asset managers, hedge funds, regional and local governments, and multilateral agencies around the world.

The Position
We are currently seeking a Modeler to join our Exposure Development team in the Model Development Group.
The Model Development group focuses on developing industry leading stochastic catastrophe models for the quantification and management of catastrophe risk. Within this group, the Exposure Development team focuses on developing data sets of economic and insured property exposures for our natural catastrophe models. Such products are essential not only for the model development process, they also are a key component of the RMS product line and provide a wealth of valuable information for our clients.
The candidate will be working in a multidisciplinary environment with catastrophe risk modelers in other teams and across different time zones (California, London, and India). He or she will be engaged in the full scope of exposure data development, from primary research to implementation to market release and post-adoption client support. The candidate will be expected to gain and further utilize an in-depth knowledge of the RMS products and relevant technologies.
Key responsibilities of this role will include:
Developing high-resolution data sets of building stock in various geographies around the world, leveraging public and/or open-source data where available;
Creating valuation models for various types of buildings and infrastructure, and integrating these with building stock data sets to develop models of economic exposure;
Researching insurance market practices, including penetration rates and prevailing policy terms and conditions, to create exposure data sets specific to the insurance industry.

Requirements
Post-graduate / Masters/Doctorate in a field related to science or engineering, including but not limited to: Civil/Structural Engineering, Urban Planning, Geographic Information Systems, Financial Engineering, Statistics, or Computer Science;
2 to 5 years of experience in creating quantitative models using large data sets (SQL, R, Python, Matlab, or similar) with a significant geospatial component;
Project management experience, and the ability to work collaboratively with a team of colleagues across groups and offices;
Excellent written and verbal communication skills evidenced by presentations at meetings and conferences with both technical and non-technical audiences.

Preferred
1 to 5 years of analytical modeling experience in the insurance, resilience, or disaster risk reduction fields
Experience in creating analytical models with data from official sources (e.g. Census, tax/property data) and/or open-source data (e.g. OpenStreetMap)
Familiarity with tabular and spatial data sets commonly used for modeling exposure and risk: population (GPW, GHSL); socioeconomic (World Bank, UNDP); and physical/environmental (MODIS, Nighttime Lights, satellite imagery)
Knowledge of building construction practices across countries, with an interest in the social and cultural contexts that guide growth and development
Understanding of the characteristics of property insurance markets around the world, including common practices around policy terms, such as limits, deductibles, and coverage types.
Education: Any Graduate
Industry: Consulting Services

Skills Required