Consultant I- R&D Atmospheric Perils
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- Mumbai, Maharashtra
- Permanent
- Full-time
- Work as part of a multidisciplinary team to develop and enhance probabilistic catastrophe models for atmospheric perils, with a primary focus on severe convective storms, hailstorms, and tropical cyclones. This includes designing and implementing hazard and scenario modelling, building event sets and vulnerability components, and integrating models into the loss calculation platform (ELEMENTS).
- Design and implement innovative methodologies to integrate climate change research into catastrophe models for re/insurance industry applications.
- Apply AI and machine learning techniques to enhance hazard modeling, data analysis, and predictive capabilities for atmospheric perils.
- Work with large meteorological and climate datasets (e.g., reanalysis, model outputs, radar/satellite and observational data) including processing, quality control, and basic analysis.
- Collaborate closely with Impact Forecasting R&D and software engineering teams throughout model development, testing, validation, and deployment stages.
- Proactively engage with stakeholders—including global R&D and analytics teams, brokers, clients, and academic partners across APAC, US, and Europe—to exchange expertise and ensure alignment.
- Stay up-to-date on developments in atmospheric perils, climate change research, and AI/ML applications within the field, and proactively share relevant insights with the team.
- Help clients and stakeholders improve model understanding and adoption by producing clear technical materials such as presentations, technical documents, and white papers.
- PhD or Master’s in Atmospheric science, Climate science, Meteorology, Ocean science or a related field.
- 2-4 years of relevant experience in insurance or risk assessment industry with proven track record of developing or evaluation of catastrophe models is an advantage.
- Strong foundation in mathematics, probability and statistics.
- Experience with dynamical models or climate models or processing/downscaling large climate data sets is a plus.
- Experience with AI and machine learning techniques applied to catastrophe risk or hazard modeling is a plus.
- Proficiency in one or more programming languages such as R, Python, or similar, with the ability to develop and implement complex algorithms.
- Basic skills in spatial data analysis using ArcGIS/QGIS or any other software.
- Proven ability to work effectively in a team as well as independently, with strong analytical and problem-solving skills and the ability to manage projects and meet deadlines.
- Strong interpersonal and communication skills (written and verbal) in English, with the ability to interface confidently with stakeholders at different levels and across business units.
- Experience in severe convective storm and hail hazard modeling, using radar and other high-resolution observational datasets, will be considered an advantage.