Data Science Intern, NA Integrated Analytics (2027 Summer - New York)

Munich Re•New York, NY

11d•$44 - $54•Hybrid

About The Position

This internship placement provides an excellent opportunity to practically apply classroom and technical training in the reinsurance industry. Interns will be coached by experienced industry professionals, exposed to Munich Re leadership, challenged as a valuable team member and contributor doing meaningful work, and mentored to develop a solid foundation that will help position them as future leaders in the field. The role involves developing solutions that allow easier access to insurance and healthier lifestyles, building highly scalable products with best security, ML, DevOps practices, researching bias and fairness, disease models, NLP, agentic LLM solutions, and more. It offers diverse career paths with leadership opportunities, flexible remote/in-person work with a focus on work-life balance, and the chance to be part of a fast-growing team that values transparency and diversity.

Requirements

Undergraduate or Graduate degree in Computer Science, Statistics, Data Science/Analytics, Applied Mathematics, Engineering (Physics, Bioinformatics) – or equivalent program offering coursework manipulating large datasets.
Comfortable working with and combining disparate and varied data sources.
Familiarity working with analytics through the modeling lifecycle including gathering data, design, recommendations, testing, implementation, communication, and revisions.
Experience working with any of the following: python, SQL, or R (familiarity with python is required, and multiple languages considered an asset).
Solid communication skills; spoken & written, formal/informal presentation.
Resourceful and able to learn quickly.
Proven ability to thrive in a dynamic environment.
Current student returning to in-class studies upon completion of the internship.
Ability to relocate to the greater New York area for a hybrid working model of at least 3 days a week in office.

Nice To Haves

Experience using git and an AI coding tool such as Claude Code or Codex.
Experience working with LLM APIs and/or building agents.
Previous exposure to insurance or financial services environment.

Responsibilities

Supporting the development of statistical, machine learning, and GenAI techniques to assist with building models for underwriting, pricing, and claims management.
Assist in building and implementing solutions that enable operational units to improve quality and speed of core processes in order to generate incremental revenue or reduce expense.
Help research new ways of modeling data to unlock actionable insights or improve processes.
Collaborate across Munich Re functions to understand how analytics can influence business decisions.
Network with existing data science groups at Munich Re.