2026 Graduate Data Science Summer Internship Program

Liberty Mutual InsuranceBoston, MA
91d

About The Position

It’s a data-driven world. Be part of a growing community of data science professionals that harnesses the power of data to analyze performance trends, identify opportunities, and keep Liberty Mutual moving forward. Calling all aspiring data scientists! Here’s the perfect opportunity to grow your knowledge and skills in key areas such as computer vision, GenAI, machine learning, and various modeling techniques and software. In this 11-week Data Science Graduate Summer Internship Program, you’ll build robust models and use statistical software, such as R, Python, and SAS, to solve critical business problems in product management, claims, distribution, marketing, HR, legal, finance, and other business functions. At the conclusion of your summer internship, you’ll deliver a presentation of your work and skills to your colleagues and the data science management team. The Data Science Graduate Summer Internship Program may be your first step toward pursuing a rewarding career at Liberty Mutual, one of the leading property and casualty insurers in the United States. Our interns often transition into full-time data scientists at our Boston Headquarters. Note: We encourage interested candidates to apply promptly, as the role may be unposted once we’ve received a sufficient number of candidates. We conduct interviews and extend offers on a rolling basis.

Requirements

  • Pursuing a Master’s degree or Ph.D. in Mathematics, Statistics, Data Science, Economics, Operational Research, Computer Science, or a related field.
  • Proven statistical, mathematical, computational, and analytical skills.
  • Completed doctoral qualifying exams (preferred).
  • Record of academic achievement.
  • Solid oral, written, communication, and interpersonal skills.
  • Proficiency in statistical software such as R, Python, and SAS.

Nice To Haves

  • Programming skills.

Responsibilities

  • Build robust models to solve critical business problems.
  • Use statistical software such as R, Python, and SAS.
  • Analyze performance trends and identify opportunities.
  • Deliver a presentation of work and skills to colleagues and management.

Benefits

  • Comprehensive benefits.
  • Continuous learning opportunities.
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