POSITION: Data Science Intern, NA Integrated Analytics (2022 Winter or Summer – New York)
LOCATION: New York, NY
ANTICIPATED START DATE: Winter 2022 or Summer 2022
NUMBER OF POSITIONS: 4
APPLICATION DEADLINE: September 27, 2021
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.
In keeping with our global position as an industry leader and innovator, Munich Re is driving transformative change in the life insurance industry through data science. You’ll work closely with Data Scientists, Data Engineers, and Actuaries – who are all experts in their fields; both locally and across other Integrated Analytics hubs. You’ll be immersed in real-time business problems while engaged in a collaborative approach to delivering world-class, innovative solutions for our North American operations.
To learn more about the North American Integrated Analytics team, please visit our site:
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.
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:
- 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).
- 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, Hadoop, 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.
Munich Re’s track record as one of the world’s leading reinsurance companies is based on a solid capital foundation, in-depth risk expertise and market know-how. Our data, our technology, and our teams place us in a unique position to lead the change to redefine the nature and impact of reinsurance for the future. We’re investing strategically in our world class talent, offering our employees a diverse and challenging work environment which promotes professional development, innovation, and passion – and rewards high performance.
Please note that only candidates who are selected for interview will be contacted directly.
We thank all candidates for their interest.