Daniel Kohlsdorf
Machine Learning Engineer at hive.app
Bremen, Free Hanseatic City of Bremen, Germany
Summary
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SeniorDaniel Kohlsdorf is a Staff Data Scientist based in Bremen with a decade of experience building production ML systems for logistics, e-commerce, and social platforms. He blends industry-grade expertise from roles at Hive, Meta, Shopify and XING with academic depth from a PhD in Computer Science at Georgia Tech, specializing in time series and audio data mining. Daniel is comfortable taking models from research to scale—working on audience targeting, recommender systems, and email marketing—while also maintaining a long-term research thread in unsupervised machine learning for dolphin acoustic communication. His background spans recommender and web mining, wearable computing, and deep learning, enabling cross-domain solutions that balance analytics, modeling and software engineering. Notably, he sustains parallel research work with the Wild Dolphin Project, applying production ML techniques to biologically driven audio datasets. Colleagues describe him as a pragmatic scientist who navigates both experimental research and high-impact product delivery.
10 years of coding experience
Github Skills (13)
audio10
machine-learning10
unsupervised-learning10
dolphins10
gcloud10
data-science9
deep-learning9
word2vec5
java4
rust3
hidden-markov-model2
python2
generator1
Programming languages (5)
Github contributions (5)
dkohlsdorf/RustWord2Vec
Mar 2019 - May 2020
Word2Vec implementation in Rust
Contributions:11 commits, 1 PR, 5 pushes in 1 year 2 months
rustword2vec
dkohlsdorf/wdp-ds
Oct 2019 - Jan 2023
Data Science For The Wild Dolphin Project
Contributions:22 releases, 1292 commits, 91 PRs in 3 years 3 months
data-sciencedolphinsaudiogcloudmachine-learning
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