Data Scientist / ML-engineer with a passion for Machine Learning and Deep Learning. Motivated by creating value through ML-solutions. Looking for new challenges and new knowledge.
Based in Norway, I'm excited to relocate and grow in a new environment.
I enjoy taking on new challenges, recently completing a full Ironman. It required consistency, resilience and preparation. I'm looking forward to bringing that mindset into a new team.
University of Bergen
Master´s Degree in Machine LearningI completed a Master’s in Machine Learning with a GPA of 3.71, focusing on topological methods in AI. My thesis, Vectorizing Distributed Homology with Deep Set of Set Networks, explored new ways to represent topological features in machine learning models. I took courses in machine learning, reinforcement learning, topological data analysis, and geometric deep learning.
GPA: 3.71
University of Bergen
Bachelor’s Degree in Theoretical MathematicsI studied Theoretical Mathematics with a GPA of 3.78, finishing with a thesis on Minimum Spanning Trees in Hierarchical Cluster Analysis, exploring how graph theory connects with data clustering. I took courses in linear algebra, discrete math, topology, probability, statistics, algorithms, and data structures.
Data Scientist/ML Engineer
TietoEvrySummer Intern (2 Summers)
Norwegian Defence Research EstablishmentStudent Teaching Assistant
University of BergenGroup sessions, exam prep and assignments grading. Held crash courses at the end of semesters.
AI Explore
Next-Gen AML PlatformAtlas
Large Financial ModelInternal LLM Service
Internal LLM PlatformYoungAI
Board Member & Event ManagerI’m a board member and event manager at YoungAI, a volunteer-run community for young professionals in AI/ML in Bergen. We organize talks, workshops, and social events to help people connect and stay up to date in the field.
I’ve given presentations through YoungAI on topics ranging from technical deep dives like equivariance in temporal graphs to more informal talks about life as a data scientist. I help lead planning and event organization. In general do work to keep our community active and inspiring.
CEDAS Hackaton Winner
CEDAS & EvinyMe and a team from YoungAI won the CEDAS & Eviny hackathon with a custom designed GRU-based model that predicted electric vehicle charging behavior using real data from Eviny. The model combined forecasting with deep embedding analysis of time series patterns, helping uncover meaningful clusters for later use. It was recognized for both its accuracy and technical depth.