Spring 2027 Intern - MAGNet Program @ Georgia Tech OMSA

Overview

As a State Farm intern, you will have the opportunity to collaborate with experienced professionals, contribute to meaningful projects, and make a real impact. Our internship program provides students with valuable training, mentorship, and networking opportunities while being fully immersed in the day-to-day operations of a Fortune 50 company. At State Farm, we believe our interns are the future of our company, and we are committed to helping you succeed! The Modeling and Analytics Graduate Network (MAGNet) program is a unique multi-semester internship opportunity designed to prepare graduate students for a full-time data science position at State Farm. Throughout their time in the program, MAGNet interns apply their predictive modeling and analytical skills to a variety of data science problems to augment their theoretical coursework while also developing professionally. It is not feasible to expose interns to the full variety of topics they need to be familiar with for full-time data science work in a single semester. As such, the MAGNet internship is designed to last the duration of an intern's graduate studies with renewal on a semester-by-semester basis. This means that while this position is hiring for the Spring 2027 semester, the intern may be invited to return for following semester(s), based on the intern's growth and progress relative to the internship's expectations. To continue in the MAGNet program, it is expected that an intern continue to renew their internship throughout their graduate program for the Spring, Summer, and Fall semesters as applicable. If you are looking for a summer or other short-term internship, MAGNet is not the right fit for you, but you may be interested in State Farm's summer internship programs. Graduate students at the Georgia Institute of Technology (GT) in the Online MS Analytics (OMSA) program are considered. While participating in the MAGNet program, students are evaluated and given consideration for full time,