Luuk Kaandorp
Medior Data Scientist
Amsterdam, North Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolLuuk Kaandorp is a Medior Data Scientist based in Amsterdam with eight years of professional experience and a Master's in Artificial Intelligence from the University of Amsterdam. He has progressed from developer roles into applied data science at Albert Heijn, focusing on NLP, recommender systems and practical AI solutions that bridge research and production. His background includes an MSc thesis project at RTL and hands-on development experience at Triple, giving him a mix of engineering discipline and product awareness. Comfortable working end-to-end, Luuk combines principled ML knowledge with pragmatic experimentation to deliver customer-facing intelligence in retail contexts.
8 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS, Informatiewetenschappen (Information sciences), Bachelor of Science - BS, Informatiewetenschappen (Information sciences) at Vrije Universiteit AmsterdamVWO, Economie & Maatschappij, VWO, Economie & Maatschappij at Petrus Canisius College (PCC)Master, Artificial Intelligence, Master, Artificial Intelligence at Universiteit van Amsterdam
Github Skills (63)
gridview6
mapbox-android6
tinder6
multi-agent6
python6
semantic-search6
java6
ai5
listview5
annotation-processing5
dialog5
agent-framework5
large-language-models5
information-retrieval5
retrieval-augmented-generation4
Programming languages (8)
Github contributions (5)
S2-group/android-apps-benchmark
Feb 2020 - Jun 2020
Bachelor project of Luuk Kaandorp for the study Information Sciences (previously IMM) at the VU Amsterdam. In collaboration with Ivano Malavolta.
Contributions:72 commits, 3 pushes in 4 months
amsterdamvu-amsterdamimmcollaborationbachelor-project
ioverho/meta-learning-emotion-detection
May 2021 - May 2021
Research project for the 2021 edition of "Advanced Topics in Computational Semantics" at the University of Amsterdam. Topic is "Mitigating Label Mismatches across Emotion Detection Datasets using Meta-Learning"
Contributions:15 commits, 15 pushes, 1 branch in 20 days
emotion-detectionmeta-learning
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