Senior Catastrophe Modeling Analyst - Hybrid, Night Shift

RecruitNest Consulting

Pasig

Hybrid

PHP 670,000 - 1,228,000

Full time

3 days ago

Be an early applicant

Application generator

Don’t send a generic resume — generate a resume and cover letter tailored to this exact role.

Get past ATS filters

Job summary

RecruitNest Consulting in Pasig, Metro Manila, is seeking an Insurance - Catastrophe Modeling Senior Analyst to support CAT modeling, data preparation, and exposure management for US non-life insurance data. You will analyze property exposure to disasters, validate and clean data, and collaborate with clients and internal teams to drive risk insights.

The ideal candidate has 2+ years in non-life insurance, strong Excel skills, and familiarity with CAT modeling tools (RMS, AIR/Touchstone,

Qualifications

Bachelor's degree in Mathematics, Statistics, Computer Science, or a related field.
2+ years of experience in Non-Life Insurance (Property, Commercial Insurance, Homeowners, or related).
Experience in CAT Modeling, Exposure Management, Insurance Risk Analysis, Underwriting, or Insurance Data Analysis.
Strong understanding of US geography: states, cities, ZIP codes, addresses, property locations.
Knowledge of natural disaster risks: hurricanes, tornadoes, earthquakes, floods, severe storms.
Experience handling policy, property, coverage and location data.
Advanced MS Excel skills: PivotTables, XLOOKUP/VLOOKUP, INDEX-MATCH.
Experience with RMS, AIR/Touchstone, Verisk is highly preferred.
Power BI, SQL, Python, or VBA is an advantage.

Responsibilities

Analyze US non-life insurance data including property, policy, coverage, and location information.
Clean and validate data for accurate addresses, ZIP codes, property details, and geographic information.
Prepare data for Catastrophe (CAT) modeling.
Analyze property exposure to hurricanes, tornadoes, earthquakes, floods, and severe storms.
Identify risk concentrations and potential losses across US states and locations.
Review CAT modeling results and prepare risk, exposure, and portfolio reports.
Perform data quality checks and investigate discrepancies.
Work with large datasets to identify trends, risks, and data errors.
Collaborate with clients, underwriters, and internal teams to resolve data and technical issues.
Support process improvements through automation and documentation.
Handle complex analysis and mentor junior team members.