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dClimate

dClimate

www.dclimate.net

1 Job

24 Employees

About the Company

dClimate is the world’s first transparent, decentralized marketplace where climate data, forecasts, and models are standardized, monetized, and distributed. The marketplace connects data publishers directly with data consumers, making climate data more accessible and reliable. When data providers share data and forecasts with the market it is automatically scored for reliability, which helps consumers to shop for information. In exchange, dClimate creates a simple, direct-to-consumer distribution mechanism to monetize their work.

Make sure to follow dClimate on Twitter @dClimateNet and join the Telegram chat: t.me/dclimatechat

Listed Jobs

Company background Company brand
Company Name
dClimate
Job Title
Climate Scientist - Catastrophe Modeler
Job Description
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.

We are open to accepting candidates from the United States and United Kingdom.

What You'll Be Doing

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.

What You'll Need
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.

What's Great to Have
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.
United Kingdom
Remote
03-03-2025