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2023 – Present
Senior Data Scientist & AI Advisor
Deutsches Biomasseforschungszentrum (DBFZ). Leipzig, Germany

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.

Experience

Over the last decade I have paired a passion for physics with hands-on work in data science and machine learning. At the Deutsches Biomasseforschungszentrum (DBFZ) I advise research teams on AI strategy, design data pipelines, and help scale HPC infrastructure. In parallel, I have spent years mentoring students, organising outreach programmes, and strengthening the communities around scientific experimentation and data literacy.

I enjoy bridging research and application—translating scientific questions into robust tooling, and making sure teams have the knowledge, processes, and infrastructure required to innovate responsibly.