Senior Data Scientist & AI Advisor

My Role at DBFZ & KIDA

I work on applied data science projects at the Deutsches Biomasseforschungszentrum (DBFZ), including contributions to the interdisciplinary KIDA project. I support research groups at DBFZ and partner institutions in turning complex datasets into robust scientific and policy-relevant results. My role blends strategic AI advisory work with hands-on implementation across the machine-learning lifecycle.

Key responsibilities

• Design data and ML strategies aligned with project goals, funding constraints, and ethical guardrails.
• Provide AI guidance for researchers, from problem framing to evaluation and publication.
• Co-shape the institute’s AI-HPC roadmap and select tooling/infrastructure balancing performance, cost, and maintainability.
• Plan and help build shared HPC/AI infrastructure across multiple institutions in the KIDA consortium.
• Apply probabilistic methods in small, practical ways to better represent uncertainty in policy-facing ML results.
• Operate Slurm clusters, container stacks, and GitLab/GitHub automation, including CVE-driven patching and security monitoring.
• Develop open-source tools like ScrAIbe and ScrAIbe-WebUI so non-coders can use transcription and diarisation pipelines.
• Advise IT staff on translating research and infrastructure plans into stable production services.
• Advise Bachelor’s and Master’s theses and contribute to project and grant applications.

This work lets me connect my theoretical physics background to real-world impact—using ML to clarify, not obscure, scientific insight.