Climate Scientist

dClimate is seeking a Climate Scientist/Catastrophe Modeler to enhance hazard and loss modeling, focusing on climate risks for the insurance and reinsurance sectors. The role requires advanced knowledge in meteorology or data science, proficiency in Python and machine learning, and experience with climate data. Responsibilities include developing models for various hazards, collaborating with clients, and communicating complex concepts. A Master's or Ph.D. in a relevant field is required.
Job Title: Climate Scientist/Catastrophe Modeler

Position Overview: We are seeking a highly motivated and technically skilled Climate Scientist/Catastrophe Modeler to join our team. The ideal candidate will have a strong foundation in meteorology, climate science, or data science, coupled with technical expertise in Python programming and machine learning. This role will play a pivotal part in advancing our hazard modeling, loss modeling, and climate scenario research, with applications in the insurance and reinsurance industries, as well as risk management teams more broadly.

Key Responsibilities:
• Hazard Modeling:
• Enhance flood modeling capabilities, either by developing in-house solutions or integrating external tools.
• Improve severe convective storm (SCS) modeling
• Contribute to earthquake and tsunami modeling, exploring new methodologies and frameworks.
• Advance tropical cyclone modeling.
• Collaborate with internal teams on multi-hazard modeling initiatives.
• Loss Modeling:
• Calibrate and validate damage models against a diverse range of data sources, including historical claims data, engineering and materials research, government data, and more.
• Reimagine portfolio calculations for probable maximum loss (PML) by developing region-wide simulations and integrating event-based loss calculations.
• Enhance our overall loss modeling framework by integrating advanced quantitative methods, Bayesian statistics, extreme value theory, and machine learning where applicable.
• Climate Scenario Research:
• Build and refine statistical and machine learning models, such as LSTMs, to project SCS perils and other climate-related risks.
• Explore climate scenarios beyond CMIP6 frameworks to better capture future risks, including more short-term scenarios.
• Cross-Functional Collaboration:
• Work closely with insurance and reinsurance clients to tailor solutions for financial risk analysis.
• Prepare detailed reports and presentations for internal stakeholders and clients.
• Act as a subject matter expert on climate change risk and catastrophe modeling, effectively communicating complex concepts to non-technical audiences.

Required Skills and Qualifications:
• Advanced degree (Master’s or Ph.D.) in Meteorology, Climate Science, Data Science, or a related field.
• Strong proficiency in Python for data analysis, modeling, and machine learning applications.
• Demonstrated experience with machine learning projects; AI experience is a plus.
• Knowledge of meteorology, climate modeling, and catastrophe modeling.
• Familiarity with industry-standard catastrophe modeling tools.
• Experience working with climate data is highly desirable, such as ERA5 Reanalysis, radar data, CMIP6 data.
• Strong analytical and problem-solving skills, with an ability to handle complex datasets.
• Excellent communication skills, both written and verbal, for effective collaboration and presentation of results.

Preferred Experience:
• Prior experience within the catastrophe modeling space.
• Hands-on experience with flood modeling, including hydrology and hydrodynamic modeling techniques.
• Familiarity with financial modeling for insurance/reinsurance purposes, including PML calculations.
• Contributions to published research or demonstrated project work in climate science or catastrophe modeling.

What We Offer:
• Opportunity to work on cutting-edge hazard and climate modeling projects with real-world applications.
• A collaborative environment where your contributions will directly impact strategic goals.
• Support for continued professional development and research initiatives.
• Competitive compensation and benefits package.