Climate Hazard Modeling, VP
MSCI · New York City
- Build physical climate risk models using state-of-the-art methodologies including AI numerical weather prediction applied to climate applications; stochastic ensembles; earth observing foundation models; as well as traditional physics-based models.
- Collaborate with our climate scientists, hydrologists, fire scientists, data scientists, and data engineers to translate business requirements into scientific solutions.
- Partner with data, cloud, and security teams to design scalable and maintainable scientific modeling pipelines.
- Foster a culture of scientific rigor and excellence in model design, including conducting validation studies to guide continuous improvement of those models.
- Lead a team of scientists to architect and implement models for climate risk assessment.
- Create robust, reproducible physical models which will stand up to peer review and validate well globally in a changing climate.
- Lead the establishment of standards, methodologies, and techniques for modeling physical risk, including how it is changing due to climate change.
- Organize and facilitate team activities for tracking work progress, communicate with internal stakeholders in product and sales teams, and align timelines and deliveries with project managers.
- Coordinate with other internal stakeholders as necessary to facilitate product requirements, deadlines, compute resources, etc.
- Ph.D. in Meteorology, Atmospheric Sciences, Oceanography, Hydrology, Physics, Engineering, Mathematics, or similar subjects.
- 5+ years of experience in roles developing environmental products to meet client requirements, with a preference for probabilistic risk products including, but not limited to, catastrophe model outputs.
- Programming experience in Python, R, C/C++, and/or Fortran.
- Experience with cloud optimized geospatial formats such as Cloud Optimized GeoTIFF (COG), GeoParquet, and related standards.
- Knowledge of the Coupled Model Intercomparison Project (CMIP) outputs and its shared socioeconomic pathways.
- Practical experience using AI tools (i.e. Claude Code, Codex) for writing production scientific code and pipelines.
- Familiarity with financial services and index space would be a plus.