I work as a Data Scientist at NORCE Analytics, an applied data science team operating across the research divisions at NORCE. Here, I develop and manage machine learning models. I have extensive experience in data analysis, statistical modeling, and operational management of models in production. My focus is on robust and automated solutions, as well as effective model governance, to ensure model quality, stable operations, thorough documentation, and compliance with regulations. Explainability is also one of my main interests.
I hold a PhD in space physics and was affiliated with the Birkeland Centre for Space Science for nine years. I defended my dissertation in 2019 and subsequently worked as a postdoctoral researcher. My research focused on asymmetries between the northern and southern hemispheres and the coupling between the solar wind, magnetosphere, and ionosphere. Among other things, I studied how the displacement of auroras in the north and south evolves over time. My research involved working with large datasets, including global auroral images, satellite measurements, ground-based observations, and 3D fluid simulations. This gave me broad experience in data architecture, cleaning, preprocessing, analysis, modeling, and dissemination.
Before joining NORCE, I worked as a Data Scientist at the Norwegian Tax Administration, where I developed and managed predictive machine learning models. My work included model development, maintenance, quality monitoring, A/B testing, model governance, and documentation. I collaborated closely with the legal department to ensure compliance with data privacy regulations and was responsible for communication with both users and leadership.
