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Intern Consultant Data Science and AI (m/f/d)*

Munich Re · Remote · Munich

Job description

Location Munich, Germany Job type Full-Time Work mode On-site Job level Internship & Working Student Job ID 11926 Company Munich Re Employment type Temporary Area of expertise Data, BI & Analytics

Are you passionate about Machine Learning and eager to develop cutting-edge AI solutions that shape the future of Munich Re and the insurance industry? Do you thrive on learning and tackling new technical challenges in a business context? If so, this internship is perfect for you!

The Data and Analytics division (DAA1) is Munich Re's hub for data, analytics, and AI-driven innovation. DAA1 leverages big data and artificial intelligence to drive decision-making and enhance operational efficiency.

Within DAA1, the Central Analytics department focuses on both enabling Munich Re’s organization for AI as well as driving implementation of important projects: We provide strategic and operational guidance to our business units, support the implementation of use cases for internal and external clients, and design, organize and implement various courses in our Data & AI Academy for internal colleagues. Additionally, we drive central strategic projects as the CDAIO office of Munich Re.

Your Job

  • Our department is looking for interns to support our highly motivated and ambitious team in driving the AI into the organization. Depending on your experience and preferences, various focus areas are possible.
  • Strategic consulting and project management support for central and business initiatives with focus on AI
  • Preparation of communication towards our internal and external stakeholders, e.g. presentations, articles, user guides
  • Implementation of use cases as part of our enablement support for business units – both “traditional data science” as well as generative AI
  • Organization and implementation of new courses for our Data & AI Academy as part of our learning offering

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, preferably in Python or R.
  • Additional experience in no code/low code software tools for data visualization, data engineering, data science and AI is a plus (tools such as PowerBI, Tableau, Alteryx, Dataiku).
  • Highly motivated with a hands-on mentality

Other requirements

  • You are available for an internship duration of at least 5 months or longer.
  • If desired, part-time work can be arranged after an initial full-time period of at least 3 months.
  • Please note that this in an on-site role at our Munich office. Limited remote work will be possible depending on project needs.

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

Silke Rößler / 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.

Your Benefits

With us, you get more than just an exciting job. Enjoy a wide range of employee benefits tailored to your wellbeing and development. Please note that regional differences may apply.

Competitive Salary

We provide fair and competitive compensation that reflects your performance and commitment.

Company performance-based Incentives

In addition to your salary, our variable compensation approach allows you to share in Munich Re's success.

Recognition and Special Rewards

We recognise outstanding individual contributions through a variety of targeted rewards and incentives.

Retirement Planning

We support your long-term financial wellbeing with retirement solutions aligned with local regulations.

Inclusive Workplace Culture

We foster a respectful, inclusive, and values-driven environment.

Learning & Development

We offer tailored learning opportunities with a strong focus on core skills and business-critical knowledge.

Work-Life-Balance

Supporting your ability to balance family, leisure, and your career.

Health & Wellbeing

We support your physical and mental health through a range of programs and activities in each location.

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