I am a Data Scientist & AI Engineer at Provinzial, where I work on the enterprise GenAI platform, document processing, RAG, MCP infrastructure, and domain-specific AI products. I translate business needs into AI use cases, design end-to-end solutions, carry out compliance assessments, and seek to promote GenAI adoption across the organization.

I am driven by a deep curiosity and approach my work with a scientific mindset. I enjoy hard problems, cross-team collaboration, and constantly learning new things.

I hold a Ph.D. in Accounting from the University of Münster. In my research, I have focused on measurement problems in accounting. I have designed and taught courses on machine learning, data literacy, and insurance economics.

1. GenAI & Agents
   Agent Frameworks & Protocols: Pydantic AI, Model Context Protocol
   AI Evals: Pydantic Evals
   LLM Platforms: Microsoft Foundry, Amazon Bedrock
   Retrieval & Search: Elasticsearch

2. Machine Learning & NLP
   Machine / Deep Learning: scikit-learn, PyTorch, transformers
   Causal Machine Learning: DoubleML
   NLP & Labeling: spaCy, Prodigy
   Data Wrangling: tidyverse, pandas

3. Backend & Platform
   APIs & Auth: FastAPI, OAuth 2.0
   DevOps: Docker, Kubernetes, Argo CD

4. Streaming & Observability
   Event Streaming: Apache Kafka
   Instrumentation: OpenTelemetry
   Traces & Logs: Dynatrace, Kibana