FM Global is a leading property insurer of the world's largest businesses, providing more than one-third of FORTUNE 1000-size companies with engineering-based risk management and property insurance solutions. FM Global helps clients maintain continuity in their business operations by drawing upon state-of-the-art loss-prevention engineering and research; risk management skills and support services; tailored risk transfer capabilities; and superior financial strength. To do so, we rely on a dynamic, culturally diverse group of employees, working in more than 100 countries, in a variety of challenging roles.
This position is for a limited term of up to three years, renewable each year. The role is typically focused on performing publishable work as part of a strategic research program under the guidance of a program manager or other senior research staff member(s).
The person in this position will be conducting research in natural hazards leading to property losses, with strong desire to expand research experience and bring expertise and innovative leadership in the following active research areas:
- Severe weather
- Tropical cyclones
- Climate change
Ideal candidates will be able to evaluate, develop, and implement novel techniques and models that will lead to impactful improvements in risk analytics and loss prevention for atmospheric and climate-related perils.
- PhD degree in atmospheric or environmental science (or related quantitative field)
- Broad physical and process-level understanding of at least one of core research areas: severe weather, tropical cyclones, wildfire, climate change
- Solid knowledge of the fundamentals of climate change including uncertainties and impacts for at least two (preferably more) key perils: extreme precipitation, drought, wildfire, riverine/coastal flooding, sea level rise, tropical cyclones, and severe weather
- Demonstrated experience using or developing global and/or regional climate models, analyzing output from global climate model ensembles, and combining large atmospheric datasets in various formats (including NetCDF, HDF, and GRIB)
- Strong analytical skills and solid knowledge of probability and statistics
- Hands-on experience using, developing, and evaluating statistical and numerical models
- Experience in writing shell scripts and using APIs for process automation, excellent programming skills in at least two programming languages including Python, R, Matlab, Fortran
- Excellent oral and written communication and presentation skills
- Solid research record (including publications)
- Experience and good working knowledge of using observations for model calibration and statistical downscaling techniques
- Experience in computer science, high-performance computing, cloud computing (e.g., AWS)
- Experience with GIS tools (ArcGIS, QGIS, GDAL)