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United States

Internship

Remote

$30/hr - $30/hr

Intern

Mercury Insurance is offering a summer internship program designed for students to gain practical work experience in the insurance field. The R&D Intern will support research initiatives and pricing strategy development, engaging in data analysis and collaborative projects while presenting findings to leadership at the end of the internship.

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Responsibilities

Utilizes Python/R/SQL/SAS or other software to extract, manipulate and analyze large sets of data in order to recommend improvements in our product pricing
Assists in predictive modeling projects and analyzing product performance under supervision and guidance; Tests new rating models to determine
Accuracy of prediction, loss ratio improvement and segmentation
Performs primary field research, including customer, distribution, competitor and insurance department under supervision and guidance
Prepares reports, graphs, charts and presentations based on research and analysis
Over the course of the summer, interns will ultimately build a minimum viable product (MVP) and have a “capstone” opportunity to present those findings to the Mercury leadership team
Other functions may be assigned

Qualification

Required

Be legally eligible to work in the U.S
Currently pursuing a BS/BA/MS in a quantitative field (Statistics, Mathematics, Data Science, Engineering, Actuarial Science, Economics/Finance)
Able to provide current GPA, as reported by your school. Minimum 3.0 GPA required, 3.5 or higher preferred
Ability to work 40 hours a week, 12-week internship, beginning in June 2026
Enrolled student attending a university program with an expected graduation date on or after August 2025
Planning to seek full-time employment between December 2026 and September 2027

Preferred

Solid track record of academic excellence
Strong commitment to teamwork, learning and collaboration
Academic or project experience in data manipulation and analysis using tools such as Python, R, SQL, SAS or equivalent
Familiarity with modeling concepts such as GLMs, logistic regression, and gradient boosting algorithms
Insurance coursework/projects; exposure to pricing/research workflows
Excellent verbal and written communication
Ability to manipulate and analyze data to address and solve business problems
Willingness to independently learn and make an impact within a team environment
Working knowledge of SQL and one language (Python or R); clear communication
SAS familiarity, dashboarding tools (Power BI/Tableau), basic model validation techniques
Proficient in Microsoft Office Suite