Catastrophe Risk Analyst

Overview: 

If you're looking for the stability of a profitable, growing company with the entrepreneurial spirit of a startup, we’re hiring. SageSure, a leader in catastrophe-exposed property insurance, is seeking a Senior Catastrophe Risk Analyst. 

In this role, you’ll play a critical part in advancing the scientific, statistical, and model-based understanding of catastrophe risk across perils such as hurricanes, earthquakes, wildfires, floods, and severe convective storms. You’ll support the development and evaluation of catastrophe models, enhance internal risk views, and deliver insights to inform underwriting, portfolio management, and reinsurance strategy. 

What you’d be doing: 

• Evaluate third-party catastrophe models (e.g., RMS, Verisk, CoreLogic) and contribute to the development of internal risk views. 
• Analyze large datasets (e.g., exposure data, claims data, hazard data) to assess model performance, validate assumptions, and identify improvement areas. 
• Conduct claims analysis, event response, and post-event analytics. 
• Support integration of climate science and emerging research into catastrophe risk analytics. 
• Collaborate with internal stakeholders (underwriting, actuarial, reinsurance, risk, and data science teams) to apply research findings to business decisions. 
• Design and implement tools, frameworks, or methodologies that improve model transparency and interpretability. 
• Monitor and interpret academic, regulatory, and industry developments in catastrophe risk science and modeling. 
• Ad hoc job duties as assigned.  

We’re looking for someone who has: 

• Advanced degree (Master’s or PhD) in Atmospheric Science, Hydrology, Earth Science, Engineering, Applied Mathematics, Statistics, or a related quantitative field. 
• 5+ years of experience in catastrophe modeling, natural hazard risk research, insurance analytics, or a related field. 
• Proficiency with catastrophe modeling platforms (RMS, Verisk, AIR, etc.). 
• Strong coding and data analysis skills (e.g., Python, R, SQL). 
• Experience working with geospatial data and tools (e.g., GIS, QGIS, ArcGIS). 
• Familiarity with stochastic simulation, probabilistic risk modeling, and related statistical methods. 
• Strong critical thinking, problem-solving, and research skills. 
• Excellent communication skills with the ability to explain complex concepts to non-technical audiences. 
• Proven ability to work collaboratively in cross-functional, research-driven environments.