Catastrophe Modeling & Data Analytics Intern (Spring 2027)

United States·Cincinnatientry

OtherData Analytics Intern

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Quick Summary

Key Responsibilities

Modeling & Geospatial Analysis Learn to use modeling software to evaluate catastrophe risk. Run analyses and identify high-risk catastrophe regions.

Technical Tools

OtherData Analytics Intern

What We Offer

~1 min read

You’ll collaborate with experienced modelers and analysts on projects such as:

We offer competitive benefits packages for full-time and part-time employees*. Full-time employees have access to medical, dental, and vision coverage, wellness plans, parental leave, adoption assistance, and tuition reimbursement. Full-time and eligible part-time employees also enjoy Paid Time Off and paid holidays, a 401(k) plan with company match, an employee stock purchase plan, and commuter benefits.

Compensation varies by role, level, and location and is influenced by skills, experience, and business needs. Your recruiter will provide details about benefits and specific compensation ranges during the hiring process. Learn more at http://www.gaig.com/careers.

Learn to use modeling software to evaluate catastrophe risk.
Run analyses and identify high-risk catastrophe regions.

Update and maintain databases, tables, queries and processes in SQL.
Review, update and maintain data engineering code in Python.
Consolidate and clean up redundant reference tables across multiple databases.

Create Tableau/Power BI dashboards.
Map wildfire, hurricane, convective storm, and earthquake events for visual insights.

Help streamline repeatable modeling processes.
Learn and apply Python for automation and data prep tasks.
Collaborate with teams to share tools and insights.

Currently pursuing a degree in Mathematics, Statistics, Data Science, Risk Management, or a related field.
Proficient with Excel and a willingness to learn SQL, Tableau, Power BI and Python.
Looking for someone who is detail-oriented, curious, and an effective communicator to join our collaborative team.

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