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

Senior Data Scientist & AI Advisor

Steering AI strategy for sustainable energy research I lead applied data science projects at the Deutsches Biomasseforschungszentrum (DBFZ), helping research groups unlock value from complex bioenergy datasets. My role combines high-level advisory work with hands-on implementation across the machine learning lifecycle. Design data and machine learning strategies that align with project goals, funding requirements, and ethical guardrails. Build and maintain reproducible analytics pipelines that empower researchers to iterate quickly without compromising rigour. Shape the institute’s AI-HPC roadmap, selecting tooling and infrastructure that balance performance, cost, and long-term maintainability. Mentor interdisciplinary teams on best practices in data governance, documentation, and collaborative experimentation. Introduce probabilistic reasoning methods and calibration routines that raise confidence in model predictions for policy-facing research. Lead the operation of Slurm clusters, container stacks, and GitLab/GitHub automation, including CVE-driven patching and security monitoring. Build open-source tooling such as ScrAIbe and ScrAIbe-WebUI so non-coders can access transcription and diarisation pipelines. This position allows me to bridge theoretical physics training with real-world impact, ensuring that machine learning accelerates rather than obscures 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.