FM is looking to solve the pressing issues of weather and climate risks by conducting groundbreaking studies on extreme weather catastrophes, including tropical cyclones, severe convective storms, and extreme precipitation, to make a tangible impact on global resilience.
Requirements
- MS in meteorology, data science or an adjacent field, with practical experience in the modelling of extreme weather, plus more than 3 years of professional experience with a good working knowledge of statistical/ dynamical downscaling techniques.
- PhD in meteorology, data science or an adjacent field with a good working knowledge of statistical/ dynamical downscaling techniques.
- Proficient in collecting, processing, and analyzing large datasets.
- Proficiency in statistical methods, including extreme value analysis and probabilistic modeling.
- Strong background in data science techniques, including machine learning (ML), neural networks and artificial intelligence (AI) methods with proven experience in developing machine learning models applied to geospatial or climate data.
- Experience writing shell scripts and using APIs for process automation, excellent programming skills in at least two programming languages including Python, R, Fortran, and/or Matlab.
- Demonstrated experience using or developing global and/or regional climate models.
Responsibilities
- Identify, plan, and conduct innovative research projects focused on extreme weather events.
- Develop and implement novel techniques and models to enhance risk analytics and loss prevention.
- Collaborate with a global team of scientists across the U.S., Singapore, and Luxembourg.
- Contribute to the development of hazard models assessing flood, wind, storms, and wildfire risks.
- Model the evolving risks and impacts of phenomena such as tropical cyclones, severe convective storms, and extreme precipitation.
- Support regional research initiatives and contribute to our global Climate Risk & Resilience activities.
- Analyze CMIP6 global climate model output, and combine large atmospheric datasets in various formats (including GeoTIFF, NetCDF, HDF, and GRIB).
Other
- MS or PhD degree in meteorology, data science or an adjacent field.
- More than 3 years of professional experience.
- Excellent oral and written communication and presentation skills.
- Ability to self-start and thrive within a high-performance team environment.
- Education: PhD in meteorology or atmospheric/ climate science with a solid research record.
