Composite Data Scientist*

At BarmeniaGothaer , who you are matters. With all your skills, ideas, and potential.
Whether you're a newcomer or bring experience to the table, you'll receive support, responsibility, and development opportunities. You'll thrive in a strong sense of community and collaboration within a team of 7,500 colleagues. As one of Germany's top 10 insurers, we operate as a mutual insurance association. Together, we're there for the people who trust us.
For us, you're not just anyone. You're someone who matters. Because you're important.

• The core of your work is the identification, prioritization and implementation of AI use cases in the composites sector together with specialist departments, process owners and our AI community network.
• You develop AI-supported components based on machine learning, NLP and generative AI, from the idea to the production-ready model.
• You analyze requirements, design solutions, and work closely with subject matter experts.
• In addition, you will ensure data availability and quality, including data profiling, ETL and close coordination with our data experts.
• Your responsibilities also include supporting the entire AI lifecycle, from development through testing and deployment (including containers and APIs) to further development and operation.
• You observe current trends in the field of Data Science & AI and actively bring relevant developments into the organization.
• You work closely with stakeholders and use-case owners, moderate workshops and ensure transparency in the process.
• Last but not least, you support the development of decentralized AI expertise in the Composites department through knowledge sharing, community work, and methodological development.

• Personally, you are characterized by your high willingness to learn, your love of experimentation, and your enjoyment of creating new things.
• Furthermore, you possess excellent communication and presentation skills for interacting with specialist departments, stakeholders and management.
• You have already gained initial experience in analyzing and evaluating the feasibility, benefits and costs of AI initiatives (including PoCs).
• You have a completed degree in (applied) mathematics, (business) informatics, data science or a comparable field.
• You also have initial practical experience with machine learning, for example with NLP, Generative AI and modern data science methodology.
• You have knowledge of data management, data profiling and ETL, ideally also of platforms like Databricks.
• You are familiar with ML methodologies such as CRISP-DM and have experience with agentic or RAG-based AI use cases.
• Good knowledge of Python, APIs, cloud-based environments and deployment (Docker, containers, GitHub) is advantageous.
• Basic knowledge of insurance processes, data protection and ethical issues surrounding AI rounds off your profile.

• Human interaction: You will experience an appreciative, open, diverse environment - genuine, competent, and with consideration for each other and for our customers.
• Flexible & family-friendly: Up to 60% mobile working, flexible working time models, 30 vacation days, the option of up to six months sabbatical and individual support for families, because life and work belong together.
• Healthy & well cared for: Strong health management, company restaurants and barista coffee bars, sports and prevention programs, as well as our confidential and anonymous counselling service if you need professional or private support.
• Learn and grow with passion: Seminars, programs, language courses and e-learning courses so you can develop professionally and personally and try new things.
• Entrepreneurial planning and protection: Partially employer-financed company pension scheme from day one, employer-financed company health insurance, group accident insurance and discounts, for example special conditions and corporate benefits.
• Sustainable & future-oriented: Germany ticket for around 25 euros per month, bike leasing, e-charging stations and opportunities to actively participate in shaping sustainability.