Jesse Anderton
Research Scientist at Spotify
United States
Summary
👤
Senior🎓
Top SchoolJesse Anderton is a research scientist at Spotify with 11 years of experience applying machine learning and software engineering to user behavior, recommender systems, and information retrieval. He developed the first practical large-scale ordinal embedding algorithms that turn relative distance orderings into Euclidean vectors for millions of points in minutes—a dramatic improvement over prior methods that failed on big datasets. His work spans academic rigor from a Northeastern PhD to production-minded engineering at firms including BlackRock and Boeing, giving him rare fluency from theory to deployable systems. At Spotify he focuses on leveraging subjective opinions and bandit-style feedback to improve recommendations and similarity search at scale. Beyond algorithms, he brings deep software craftsmanship and product sensibility from years in industry, enabling research to move into reliable, performant services. He’s particularly interested in translating large behavioral datasets into interpretable user models that directly improve retrieval and personalization.
11 years of coding experience
11 years of employment as a software developer
BS, Computer Science, BS, Computer Science at The University of New MexicoMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at Northeastern University
Github Skills (17)
deploying6
machine-learning5
watson5
tensorflow4
docker3
apache-beam3
mlflow2
mlops2
tfx1
fortran1
xsd1
xml-schema1
struct1
ml1
xml1
Programming languages (1)
Github contributions (5)
jesand/hicluster
Dec 2015 - Jan 2016
Contributions:129 pushes, 1 branch in 1 month
jesand/lloe
May 2019 - Jun 2019
Contributions:2 commits, 2 pushes, 1 branch in 1 month
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