About

I am a data scientist based in Odense. I hold a Cand.Scient. in Data Science from SDU, combined with a Bachelor's degree in Medievidenskab — media studies — which is a pairing that sounds unusual but turns out to be genuinely useful: the technical work is only as good as your ability to explain what it means to someone who did not build it.

Background

I worked as a Data Scientist student assistant at SDU RIO for two years, where most of my work was in cluster analysis, survey data, and reporting tools built in R and Power BI. After graduating I joined CyberPilot as an AI & Data Engineer, where I worked on an AWS Bedrock-based phishing campaign recommendation system — RAG pipelines, LLM evaluation across several models, and GDPR-compliant migration planning. The position was eliminated in a round of redundancies.

I am currently looking for a full-time role in data science or analytics, with a particular interest in public sector and healthcare settings where the work has clear real-world consequence.

Technical stack

Day to day: Python, SQL, R. Machine learning with scikit-learn and PyTorch. Data work with pandas, PySpark, and PostgreSQL. I have built and deployed RAG pipelines with pgvector, worked with the AWS Bedrock and Scaleway APIs, and used Power BI for reporting in institutional settings. On the infrastructure side I am comfortable with Railway, basic Docker, and Git-based deployment workflows.

Outside work

I run most mornings, which is partly why I built Daglig Vejr — checking three apps before deciding whether to take an antihistamine got old quickly. I collect vinyl records, bake sourdough with variable results, and spend more time than I should reading about IEMs.