Intern Consultant AI Governance & Strategy (m/f/d)*

The Data and Analytics division (DAA) is Munich Re's hub for Data, Analytics and AI. It drives Munich Re’s Data and AI strategy, is responsible for the key enablers data, skills, governance and technology, and coordinates Data, Analytics and AI projects to create value for our core business.

The Central Analytics department (DAA1.3) drives strategic initiatives in Data Analytics & AI, enables business & central functions through training and technology, supports Data Analytics & AI (use cases), and further develops the Insurance Analytics Platform that provides scalable Data Analytics & AI solutions according to the needs of our core business functions.

The AI Governance and Strategy section (DAA1.3.2) acts as a 1st line function for AI Governance, supports the further development of the AI strategy is responsible for the tasks of AI adoption and AI enablement, and owns the Data & AI Academy for the RI and Specialty Group.

Your Job

• Our team is looking for interns to support our highly motivated and ambitious team in driving the AI adoption at Munich Re. Depending on your experience and preferences, various focus areas are possible.
• Support the AI Governance team in their daily work.
• Preparation of communication towards our internal and external stakeholders, e.g. presentations, articles
• Organization and implementation of new courses for our Data & AI Academy as part of our learning offering
• Organizes the management of the global Data Analytics & AI community including the organization of knowledge sharing sessions and exchanges for developers and the bi-annual Data & AI conference
  
  
  

Your Profile

• Master’s studies (or final year of Bachelor's studies) with a strong academic record in a quantitative field like Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related discipline incl. business administration/economics with a quantitative focus
• Passion for AI and Data Science with a solid theoretical foundation in AI and Data Science methodology
• Excellent communication and presentation skills; consulting or project management experience is a plus.
• Ability to structure and drive complex problems on your own
• First experiences with putting AI and ML theory into practice
• Highly motivated with a hands-on mentality
  
  
  

Students from countries outside the EU require a German residence-/work permit. The first master's degree may not have been completed before/during the entire internship.

About Us

As the world's leading reinsurance company with more than 16,000 employees at over 50 locations, Munich Re introduces a paradigm shift in the way you think about insurance. By turning uncertainty into a manageable risk we enable fundamental change. Join us working on topics today that will concern society tomorrow, whether that be climate change, major construction projects, medical risk assessment or even space travel.

Together we embrace a culture where multiskilled teams dare to think big. We create the new and the different for our clients and cultivate innovation.

Sounds like you? Push boundaries with us and be part of Munich Re. Our employees are our greatest strength. That’s why we offer them a wide range of benefits. You can find some examples below.

Unlock your potential

• Diversity, Equity & Inclusion: we embrace the power of differences and are convinced that diversity fosters innovation and resilience and enables us to act braver and better.
• Continuous Learning: we believe that continuous learning is a key differentiator and critical for building new skills and accelerating growth.
• Career Mobility: we actively support career mobility, and our strong global and regional presence offers a wealth of career growth opportunities for you.
  
  
  

Münchener Rückversicherungs-Gesellschaft

Oksana Kern / Nina Hartmuth

• Coordination Students Program
• Munich Re not only stands for fairness with regard to its clients; it is also an equal opportunity employer. Severely disabled candidates will also be prioritised, if equally qualified.