Sebastian Gregorius Winther-Larsen
Sebastian Winther-Larsen is a data scientist at Menon Economics, specializing in modeling, whether in Excel or deploying applications in cloud solutions. He has extensive experience collaborating with subcontractors and clients’ internal developers to implement tailored solutions. Known for his ability to find creative solutions to complex challenges, he works across both the private and public sectors.
As a project manager, Sebastian has taken projects from grassroots level to government policy, engaging key stakeholders across various industries. His analysis of capital returns in agriculture served as foundational work for a parliamentary white paper, and he has prepared background material for a white paper on floods and landslides. Additionally, he has developed socio-economic methodologies and conducted calculations for climate adaptation and other natural hazards, working with municipalities, ministries, the Nordic Council of Ministers, and the financial and insurance industries.
Sebastian holds two Master’s degrees—one in economics and finance from the University of Bath and another in computational physics from the University of Oslo. At Menon, he has contributed to R&D projects, including advancing macroeconomic equilibrium models and transport modeling. He has supervised master’s students in machine learning, served as an examiner in artificial intelligence, and delivered guest lectures on machine learning applications in time series analysis.
Sebastian is actively engaged in helping clients understand and apply AI to enhance their services. He has developed applications based on predictive algorithms and large language models (LLMs) to uncover patterns, trends, and insights from large text datasets. His strength lies in rapidly prototyping functional AI solutions, demonstrating the practical value of AI technologies. As an internal expert at Menon, he actively contributes to raising competency levels through programming and methodology training. He is frequently involved in projects to provide expert assessments and guidance, strengthening Menon’s quantitative analysis capabilities.
Sebastian Winther-Larsen is a data scientist at Menon Economics, specializing in modeling, whether in Excel or deploying applications in cloud solutions. He has extensive experience collaborating with subcontractors and clients’ internal developers to implement tailored solutions. Known for his ability to find creative solutions to complex challenges, he works across both the private and public sectors.
As a project manager, Sebastian has taken projects from grassroots level to government policy, engaging key stakeholders across various industries. His analysis of capital returns in agriculture served as foundational work for a parliamentary white paper, and he has prepared background material for a white paper on floods and landslides. Additionally, he has developed socio-economic methodologies and conducted calculations for climate adaptation and other natural hazards, working with municipalities, ministries, the Nordic Council of Ministers, and the financial and insurance industries.
Sebastian holds two Master’s degrees—one in economics and finance from the University of Bath and another in computational physics from the University of Oslo. At Menon, he has contributed to R&D projects, including advancing macroeconomic equilibrium models and transport modeling. He has supervised master’s students in machine learning, served as an examiner in artificial intelligence, and delivered guest lectures on machine learning applications in time series analysis.
Sebastian is actively engaged in helping clients understand and apply AI to enhance their services. He has developed applications based on predictive algorithms and large language models (LLMs) to uncover patterns, trends, and insights from large text datasets. His strength lies in rapidly prototyping functional AI solutions, demonstrating the practical value of AI technologies. As an internal expert at Menon, he actively contributes to raising competency levels through programming and methodology training. He is frequently involved in projects to provide expert assessments and guidance, strengthening Menon’s quantitative analysis capabilities.
