We are the world’s largest publicly traded property and casualty insurer with operations in 54 countries, exceptional financial strength, and a broad range of personal and commercial insurance products. As an underwriting company, we assess, assume and manage risk with insight and discipline. We service and pay our claims fairly and promptly. We combine the precision of craftsmanship with decades of 

We are seeking a highly motivated and talented Actuarial Intern to join our team and work on International Accident & Health Actuarial Projects. The successful candidate will be responsible for data preparation, ratemaking and portfolio projections. The intern will also work on other automation projects as required. As a member of our team, you will have the opportunity to work independently as well as collaborate with other team members and gain valuable experience in the industry.

Responsibilities

Data manipulation and preparation for rate review in Python and SQL. Adapt GLM modeling results to loss cost models. Build various impact analysis projects in RADAR. Work on other automation projects as required.

Benefits

As part of our internship program, you will work on several International Accident & Health Actuarial Projects with a dynamic team and contribute to real-world projects. You will receive guidance and mentorship from talented Actuaries and Data Scientists and gain hands-on experience in the industry. As a part of the program, you will have the opportunity to work on business specific projects where you will gain knowledge and experience to supplement and strengthen your academic skills. Additionally, you will be offered a competitive salary and can network with professionals in the field. For those who excel in the program, we would welcome the opportunity to discuss full-time employment opportunities at Chubb after graduation.

 

 

Students pursuing an Actuarial/Statistics/Data Science degree Excellent oral and written communication skills Skillset requirement:  Microsoft Office knowledge such as Excel, PowerPoint and Power BI Proficiency in Python. Knowledge in actuarial ratemaking. Advanced statistic knowledge in GLM and tree-based ML methods.  RADAR is a plus.