About me
"Eine Durian am Stiel ist eine formidable Schlagwaffe nach Art des friesischen Morgensterns. In Thailand richtet sich die Strafe für ihren Einsatz nach der Anzahl der durch die Noppen zugefügten Wunden"
- ROLAND HANEWALD: Essbare Früchte Asiens
About Me
I am a Senior Principal Data Scientist at McKinsey & Company, based in Munich, Germany. My work focuses on artificial intelligence, agentic AI, advanced analytics, machine learning, and optimization. I help organizations translate AI into measurable business impact, from strategy and value diagnostics to implementation, scaling, and capability building.
I work primarily with industrials and infrastructure clients across Europe, North America, and South Africa. My experience covers AI strategy, agentic AI, AI-enabled business building, data and analytics transformations, analytics operating models, and the design and implementation of scalable AI solutions.
I hold a PhD in particle physics from Ludwig Maximilian University of Munich, obtained under the supervision of Nobel Prize Laureate Theodor Hänsch. During my academic career, I worked for the Max Planck Institute for Quantum Optics and CERN, the European Organization for Nuclear Research.
Details
I support industrials and infrastructure clients in identifying, prioritizing, and scaling AI opportunities across their businesses. My work combines strategic perspective with deep technical expertise, helping clients move from ambition to practical AI solutions, platforms, and capabilities.
My focus areas include agentic AI, advanced analytics, machine learning, AI product development, decision-support systems, mathematical optimization, and AI-enabled transformation programs. I am particularly interested in the interface between technical feasibility, business value, and organizational adoption.
Competencies:
- AI and agentic AI strategy
- AI use case diagnostics, prioritization, and scaling
- AI solution architecture, including agent orchestration and LLM-based application design
- AI-enabled business building
- Advanced analytics and machine learning at scale
- Data science leadership and capability building
Technical skill set:
- Cloud: certified on Azure and AWS
- Programming: Python, C++, C#
- AI frameworks: LangChain, LlamaIndex, Semantic Kernel, AutoGen
- LLM application patterns and tools: LangSmith, Ragas, DeepEval, Guardrails AI
- Machine learning frameworks: scikit-learn, PyTorch, TensorFlow
- Data and parallel computing: Spark, SQL
- Visualization: Tableau, Power BI
- Methods: ai and agentic ai engineering, machine learning, linear optimization, statistical modeling
