Marcel Kurovski
Applied Scientist (I5) at DoorDash
Munich, Bavaria, Germany
Summary
👤
Senior🎓
Top SchoolMarcel Kurovski is an applied scientist with nine years focused on deep learning and recommender systems, currently shaping personalization and ranking at DoorDash/Wolt from Munich. He has led global transformer-based restaurant and retail ranking rollouts that delivered multi-million-euro GOV uplift and optimized whole-page personalization and carousel strategies at scale. Experienced in architecting cross-domain recommenders, he previously built production DL systems for major marketplaces (including mobile.de) and industrial forecasting solutions while consulting on personalization roadmaps. Marcel mentors applied scientists, ran a RecSys/Search journal club, and shares industry-academic perspectives as host of a long-running recommender podcast with 30+ episodes. His background blends academic rigor (KIT) and product impact, and he often bridges research and engineering by turning state-of-the-art models into measurable business outcomes.
10 years of coding experience
6 years of employment as a software developer
Master's Degree Industrial Engineering and Management, Master's Degree Industrial Engineering and Management at Karlsruhe Institute of Technology (KIT)
German, English, Spanish
Github Skills (64)
python10
machine-learning10
ml10
deep-learning10
tensorflow10
deep-neural-networks10
neural-network10
tensorflow-serving9
recommender8
clustering8
word2vec7
feature-selection7
recommender-system7
bayesian7
bayesian-methods6
Programming languages (5)
Github contributions (5)
mkurovski/liked2play
Dec 2021 - Jun 2022
Contributions:15 commits, 3 pushes in 5 months
mkurovski/emnist_dl2prod
Sep 2018 - May 2019
JuPyter Notebooks and Python Package for Deep Learning Model Exploration, Translation and Deployment
Contributions:20 commits, 6 pushes, 1 branch in 7 months
deep-learningjupyter-notebookpythonmachine-learningdeployment
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