Data Science Intern, NA Integrated Analytics (2025 Summer - New York)

Company



Munich Re Life US



Location



New York
, United States

POSITION: Data Science Intern, NA Integrated Analytics (2025 Summer - New York)
LOCATION: New York, NY
ANTICIPATED START DATE: Summer 2025

Together, we engage with everything we have and are, to help humankind act braver and better.

As the world's leading reinsurance company with more than 40,000 employees in over 50 locations around the globe, Munich Re introduces a paradigm shift in the way you think about insurance. By turning uncertainty into manageable risk, we enable fundamental change. We recognize Diversity, Inclusion, and Belonging as a key priority with a culture that welcomes different thoughts and opinions. We dare to think big and are continuously innovating on behalf of our clients.

How can ML promote longer and healthier lives? Armed with decades of risk data, novel data sources, and a team of innovative data scientists, engineers, and domain experts, Munich RE is building solutions that are transforming the life insurance industry.

• Develop solutions that allow easier access to insurance and healthier lifestyles
• Build highly scalable products with best security, ML, DevOps practices
• Research bias and fairness, disease models, NLP & more
• Discover diverse careers with leadership opportunities
• Flexible remote/in-person work + focus on work-life balance
• Be part of a fast-growing team that values transparency & diversity

Our internship placements provide you with an excellent opportunity to practically apply your classroom and technical training in the reinsurance industry. While with our team, you'll 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 you as a future leader in the field.

Munich Re is operating under a hybrid working model, including 3 days in office/week with the remaining days working from home. Students are expected to relocate to the city in which they work for the duration of their co-op, so they can fully benefit from the full program integration. This provides a great opportunity to network, develop soft skills and become immersed within the greater Munich Re culture; including engaging with your team while in-office for face-to-face meetings, sharing meaningful moments, and allocating time to connect with your Manager.

To learn more about the North American Integrated Analytics team, please visit our site: https://www.munichre.com/us-life/en/solutions/integrated-analytics.html

THE ROLE:
Responsibilities may include, but will not be limited to the following:

• Supporting the development of statistical and machine learning 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.

QUALIFICATIONS:
We're looking for well-rounded individuals who are technically astute, have strong communication skills, and demonstrate the ability to build positive relationships with internal clients. We're seeking energetic and collaborative professionals who are excited to join our winning team and show promise of becoming a future leader in the data science space.

Specifically, we're looking for the following qualifications:

Technical:

• Undergraduate or Graduate degree in Computer Science, Statistics, Data Science/Analytics, Applied Mathematics, Engineering (Physics, Bioinformatics) - or equivalent program offering coursework manipulating large datasets;
• Familiarity working with analytics through the modeling lifecycle including gathering data, design, recommendations, testing, implementation, communication, and revisions;
• Familiarity with advanced predictive analytic techniques;
• Experience working with any of the following: SQL, Python, or R (familiarity with multiple languages considered an asset).

Behavioral:

• Solid communication skills; spoken & written, formal/informal presentation;
• Resourceful and able to learn quickly;
• Proven ability to thrive in a dynamic environment.

Preferred (but not required):

• Familiarity with big data technologies (ex: Apache Spark, +, etc) and deep learning models (such as tensorflow);
• Previous exposure to insurance or financial services environment is preferred but not required.

Note that this opportunity is open to current students who are returning to in-class studies upon the completion of the internship.