Arvid Lindström is a data scientist and economist with nine years of experience applying AI and analytics to SaaS strategy and pricing operations, currently leading data-driven strategy at BeyondDutch from Amsterdam. He has a track record at Beat of turning pricing strategy into production—designing a unified KPI that automated end-to-end pricing, building revenue management and time-series forecasting systems, and deploying models via Argo/Presto. Comfortable prototyping in SQL and Python and evangelising tools across stakeholders, he bridges technical implementation and business adoption to ensure analytics change day-to-day decision making. Trained in artificial intelligence (MSc, University of Amsterdam), he brings a rare blend of hands-on modeling, geospatial forecasting, and commercial impact—recently driving a geo-demand forecaster and fleet scheduling rules that materially boosted revenue per asset. Open to roles that return him to more hands-on analytical work and further grow his technical craft.
9 years of coding experience
2 years of employment as a software developer
Master of Science - MS, Artificial Intelligence, Master of Science - MS, Artificial Intelligence at University of Amsterdam
Bachelor of Science - BS, Artificial Intelligence, Bachelor of Science - BS, Artificial Intelligence at University of Groningen
Originally cloned from https://github.com/williamleif/GraphSAGE.git/ by the authors of "Inductive Representation Learning on Large Graphs" 2018 (https://arxiv.org/abs/1706.02216), this repo contains the code of a project using GraphsSAGE in order to perform inductive node classification as a graphical approach to dialogue act classification (DAC).
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