Senior Insurance Data & Risk Analyst (Hybrid)

Neksjob Philippines; Pasig; Hybrid; PHP 670,000 - 1,339,000; Full time

Benefits offered by this job

Equity incentives

Commission

Performance bonus

Incentives

Job summary

Neksjob Philippines is seeking a Senior Insurance Data & Risk Analyst for a hybrid role in Pasig. You will analyze US non-life insurance data, support CAT modeling, and help improve data quality across geographies.

Ideal candidates have at least 2 years in US non-life insurance, experience in CAT modeling and exposure management, and strong data analytics skills. You will collaborate with underwriters and clients to resolve data issues and drive process improvements.

Qualifications

• Minimum 2 years of experience in US Non-Life Insurance.
• Experience in CAT Modeling, Exposure Management, Insurance Risk Analysis, Underwriting, or Insurance Data Analysis.
• Strong understanding of US geography, including states, cities, ZIP codes, addresses, and property locations.
• Experience handling insurance policy, property, coverage, and location data.
• Experience with data cleansing, data validation, geocoding, and data accuracy checks.
• Strong mathematical, analytical, and problem-solving skills with excellent attention to detail.
• Bachelor’s/Master’s degree in Mathematics, Statistics, Actuarial Science, Insurance, Engineering, Geography, Data Analytics, or a related field.

Responsibilities

• Analyze US non-life insurance data, including property, policy, coverage, and location information.
• Clean and validate addresses, ZIP codes, property details, and geographic data.
• Prepare insurance data for Catastrophe (CAT) Modeling.
• Analyze property exposure to hurricanes, tornadoes, earthquakes, floods, and severe storms.
• Identify risk concentrations and potential losses across different US states and locations.
• Review CAT modeling results and prepare risk, exposure, and portfolio reports.
• Perform data quality checks and investigate data issues.
• Work with large datasets to identify trends, risks, and data errors.
• Coordinate with clients, underwriters, and internal teams to resolve data and technical issues.
• Help improve processes through automation, documentation, and efficiency improvements.

Skills

US Non-Life Insurance

CAT Modeling

Geography (US)

Data Analysis

Data Cleansing

Geocoding

Risk Analysis

Underwriting

Education

Bachelor’s/Master’s degree in Mathematics, Statistics, Actuarial Science, Insurance, Engineering, Geography, Data Analytics, or related field

Job description

Senior Insurance Data & Risk Analyst (Hybrid)

Hybrid - Pasig 1-3 Yrs Exp Bachelor Full-time

Job Description

Employee Recognition and Rewards

Equity Incentive Plan, Commission, Performance Bonus, Incentives

Professional Development

Job Training, Professional Development

Main Responsibilities

Analyze US non-life insurance data, including property, policy, coverage, and location information.

Clean and validate addresses, ZIP codes, property details, and geographic data.

Prepare insurance data for Catastrophe (CAT) Modeling.

Analyze property exposure to hurricanes, tornadoes, earthquakes, floods, and severe storms.

Identify risk concentrations and potential losses across different US states and locations.

Review CAT modeling results and prepare risk, exposure, and portfolio reports.

Perform data quality checks and investigate data issues.

Work with large datasets to identify trends, risks, and data errors.

Coordinate with clients, underwriters, and internal teams to resolve data and technical issues.

Help improve processes through automation, documentation, and efficiency improvements.

Qualifications

Minimum 2 years of experience in US Non-Life Insurance, such as Property, Commercial Insurance, Homeowners, or related areas.

Experience in CAT Modeling, Exposure Management, Insurance Risk Analysis, Underwriting, or Insurance Data Analysis.

Strong understanding of US geography, including states, cities, ZIP codes, addresses, and property locations.

Experience handling insurance policy, property, coverage, and location data.

Experience with data cleansing, data validation, geocoding, and data accuracy checks.

Strong mathematical, analytical, and problem-solving skills with excellent attention to detail.

Bachelor’s/Master’s degree in Mathematics, Statistics, Actuarial Science, Insurance, Engineering, Geography, Data Analytics, or a related field.