Simen Skaret Karlsen

Simen Skaret Karlsen

Data Scientist, Bergen

As a part of the StormGeo Data Science team, Simen develops advanced analytics and deep learning models for forecasting, both in the meteorological domain and for our clients in shipping and cross industry.

Simen’s Story

“These days, people are not interested in simply knowing what the weather will be like. They want to know how the weather will impact them and their business specifically. With our access to vast quantities of high quality atmospheric and oceanographic data, along with dual competencies in both MetOcean and data science, we can cut out the middle man and provide our clients with the precise insights they need, rather than just a data stream.”

After writing his Master’s thesis on Automated Front Detection in 2017, Simen joined StormGeo in Bergen as a Data Scientist on the research team. He specializes in advanced analytics and emerging techniques within AI, machine learning and deep learning. With a background in Information Science, Simen is able to develop datasets and prediction algorithms in the cross-section between meteorological and domain-specific data.

His passion for development methodology coupled with an optimism for technology has led him within the last year to take part in StormGeo’s transition from traditional modelling to advanced analytics, from on-premise data centers to the cloud, and from a monolithic development mindset to lean and agile data science.

“This is an exciting time to be part of a data science initiative. Every day, we are transforming the way we work with and think about weather data. We now create and test hypotheses at a pace that we could only dream about a few years ago, and that pace will only continue to increase as we transform our organization and apply new techniques and methods. In the end, this leads to more research and faster results, as well as more insight and value for our clients.”


Master of Science in Information Science from the University of Bergen.