We are looking for a Catastrophe Modeling Analyst to quantify catastrophe risk inward reinsurance contracts by analyzing exposure data and catastrophe model outputs. This role combines core catastrophe modeling work with data science/ML techniques (e.g., similarity scoring, clustering) to improve data quality and produce decision-ready insights.

Key Responsibilities

Run third-party catastrophe models to estimate catastrophe risk for cedents/reinsurance submissions
Validate, justify, and explain model outputs to ensure accuracy and reasonableness
Produce exposure reports that summarize cedent catastrophe exposure clearly
Support catastrophe pricing for reinsurance submissions with minimal supervision
Apply ML methods (similarity scoring, clustering) to clean, align, and analyze large exposure datasets
Deliver concise analytics outputs: written summaries, dashboards (Power BI or similar), and reproducible notebooks (Python/R)

Qualifications / Requirements

Strong analytical skills: intermediate Excel + practical Python and/or SQL (R optional)
Experience working with large, complex datasets and applying ML techniques to support data quality/alignment
Strong attention to detail and organizational discipline
Strong communication skills and ability to explain outputs to non-technical stakeholders
Basic knowledge of insurance/reinsurance terminology and interest in catastrophe modeling
Flexible and able to learn new processes quickly
Willing to work outside normal office hours during peak season (evenings/weekends/holidays)
Nice-to-have: Power BI/data visualization, exposure to ETL/pipelines/warehousing, report/process automation

Education

Graduate of a quantitative course (preferred: Mathematics, Actuarial Science, Computer Science, IT, Physical Sciences, Engineering)

Catastrophe Modeling Analyst

Data Analyst