Climate & Catastrophe Risk Analyst

Job Title:

Catastrophe Risk Modeller (Natural Perils – EQ, Cyclone, Rainfall)

Location:

Remote / Bengaluru / Mumbai

Type: Full-time | Hybrid (Open to part-time for very senior consultants)

Role Overview:

We are seeking experienced Catastrophe Risk Modellers to play a foundational role in developing BhoomiSure's in-house stochastic and parametric risk models for Earthquake, Cyclone, and Rainfall events. You will collaborate with actuaries, underwriters, technologists, and reinsurers to develop scientifically robust models that support our parametric and portfolio-level insurance products.

Key Responsibilities:

• Develop stochastic event sets for tropical cyclones, earthquakes, and excess rainfall using historical, satellite, and reanalysis datasets.
• Build and calibrate hazard intensity footprints and vulnerability models tailored to Indian and regional geographies.
• Provide loss estimation frameworks for event-based and probabilistic scenarios across various asset classes (property, infrastructure, agriculture, etc.).
• Validate, backtest, and benchmark models using historical catastrophe events and publicly available loss databases.
• Collaborate with actuarial and product teams to support pricing, structuring, and reinsurance placements.
• Create a catastrophe loss database for underwriting, regulatory, and capital modeling purposes (e.g., PMLs, AALs, Return Period Losses).
• Support the development of parametric indices by linking physical event parameters to modeled or observed loss estimates.
• Prepare technical documentation and contribute to regulatory filings and reinsurance submissions.
• Act as a Subject Matter Expert (SME) in discussions with reinsurers and technical partners.

Required Skills & Tools:

• Strong background in catastrophe risk modeling, climatology, or geophysical hazard analysis
• Hands-on experience with CAT modeling tools such as RMS, AIR, CoreLogic, or Oasis LMF
• Proficiency in Python or R for data analysis and model development
• Experience with GIS tools (e.g., QGIS, ArcGIS) and working with raster/geospatial datasets
• Familiarity with reanalysis datasets (e.g., ERA5, MERRA-2) and global hazard databases (e.g., USGS, NOAA IBTrACS, GPM)
• Deep understanding of event simulation, hazard intensity metrics, vulnerability modeling, and financial loss estimation
• Experience estimating Probable Maximum Loss (PML) and Average Annual Loss (AAL)

Preferred / Good-to-Have Skills:

• Exposure to open catastrophe modeling platforms (Oasis, CAPRA, etc.)
• Experience with parametric insurance triggers or index-based products
• Familiarity with machine learning, Bayesian inference, or ensemble forecasting for hazard modeling
• SQL/database design experience for modeling data pipelines
• Knowledge of regulatory frameworks like IFRS 17 or Solvency II

Qualifications:

Education:

Master's or Ph.D. in any of the following fields:

• Earth Sciences / Atmospheric Sciences
• Applied Mathematics / Physics
• Catastrophe Modelling / Geophysics
• Actuarial Science (with CAT risk focus)
• Environmental Engineering / Remote Sensing / Data Science (with geo-hazard specialization)

Professional Credentials (Preferred):

• Certified Catastrophe Risk Analyst (CCRA)
• Associate or Fellow of IFoA, CAS, IAI with relevant experience
• GARP SCR Certification
• Published research or open-source contributions in hazard or catastrophe modeling

Experience:

• 3–5 years in catastrophe modeling or hazard research
• 7+ years for senior positions at re/insurers, modeling firms, consulting organizations, or national disaster centers
• Experience with Asia/India-specific perils is a strong plus

Why Join Us?

• Build models from the ground up with full innovation freedom
• Help shape parametric solutions for high-impact, climate-vulnerable regions
• Collaborate with leading reinsurers and satellite data partners
• Competitive compensation, ESOPs, and research-driven culture

If you're passionate about using science and technology to solve real-world climate risks, we'd love to hear from you.