Catastrophe Modeling Analyst - Junior (MS)

Arch Global Services Philippines; Manila; On-site; PHP 600,000 - 1,000,000; Full time

Job summary

Arch Global Services Philippines seeks a Catastrophe Modeling Analyst to quantify catastrophe risk on inward reinsurance contracts, analyze client exposure, and produce decision-ready insights. You will leverage third-party models, justify CAT outputs, and generate comprehensive reports while exploring ML techniques to clean and analyze large datasets.

Expect collaboration with data teams and stakeholders. Graduate in a quantitative field, with experience in Python/SQL and data visualization.

Qualifications

• Experience with Python and/or SQL for data preparation and automation.
• Proficiency in Excel and data analysis.
• Ability to create clear written reports and dashboards for non-technical stakeholders.
• Willingness to work outside normal hours during peak season.
• Familiarity with reinsurance terminology is a plus.

Responsibilities

• Leverage third-party catastrophe models to obtain estimates of catastrophe risk.
• Justify and explain CAT model outputs and ensure they are reasonable and correct.
• Generate reports to show cedents' catastrophe exposure.
• Handle cat pricing of reinsurance submissions with minimal supervision.
• Apply ML methods to clean, align, and analyze large exposure datasets for reliable insights.
• Produce analytics artifacts – reports, dashboards (Power BI), and reproducible notebooks (Python/R).

Skills

Analytical skills

Python/SQL

Communication

Attention to detail

Data visualization

Education

Quantitative degree (Math/CS/IT)

Tools

Power BI

Excel

Python

SQL

Job description

With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility. The Catastrophe Modeling Analyst quantifies catastrophe risk on Arch Re's inward reinsurance contracts, analyzing client exposure and model outputs in third-party platforms, researching catastrophe risk, and producing clear exposure reports. In parallel, the role leverages scalable data-science and machine-learning (e.g., similarity scoring, clustering) to clean, align, and analyze large exposure datasets, producing decision-ready insights while fulfilling core catastrophe modeling duties.

Responsibilities

• Leverage third-party catastrophe models to obtain estimates of catastrophe risk of Arch Re's cedents.
• Justify and explain the CAT model outputs and ensure that they are reasonable and correct.
• Generate other reports to give a complete picture of the cedents' catastrophe exposure.
• Handle with minimal supervision the cat pricing of reinsurance submissions.
• Apply machine-learning methods (e.g., similarity scoring and clustering) to clean, align, and analyze large exposure datasets - producing reliable,decision-ready insights.
• Produce concise analytics artifacts - written reports/summaries, interactive dashboards (e.g., Power BI, etc.), and reproducible notebooks (Python/R).

Required Skills/Experience

• Demonstrated analytical proficiency: intermediate Excel and practical experience with Python and/or SQL (R optional) for data preparation, analysis,and automation.
• Excellent attention to detail and organizational skills.
• Strong interpersonal and communication skills.
• Ability to produce clear, concise written reports/summaries and dashboards (e.g., Power BI, etc.) for non-technical stakeholders.
• Interest in learning about reinsurance and catastrophe modeling.
• Ready to work outside of normal office hours during peak season, including evenings, weekends, and public holidays as necessary.
• Basic knowledge of insurance and/or reinsurance terminology.
• Flexible with changing requirements and ability to learn new processes quickly.
• Experience working with large, complex datasets and applying ML techniques to support data quality, alignment, and analytic insight generation isexpected.
• Familiarity with data visualization tools (e.g., Power BI, etc.) is nice-to-have; exposure to data engineering (ETL, pipelines, warehousing) andprocess/report automation is beneficial.

Education

• Graduate of any quantitative course, preferably in Mathematics, Actuarial Science, Computer Science, Information Technology, Physical Sciences, orEngineering.

10400 Arch Global Services (Philippines) Inc.