Kristian Kaufmann
Principal Data Scientist
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolKristian Kaufmann is a Principal Data Scientist in New York with 11 years of experience building large-scale data and ML systems that bridge software engineering, statistical modeling, and production backend services. He has driven ML and pipeline scaling at companies like Spotify and Prognos, led HBase migrations and pipeline overhauls at Vimeo, and boosted recommendation engagement through probabilistic engines and A/B testing at nRelate. Comfortable across Python, Scala, C++, and cloud-native Spark/BigQuery stacks, he also contributes to open-source data infrastructure—improving Maxwell’s MySQL-to-Kafka consistency and schema handling. Trained as a PhD chemist with deep computational modeling roots, he brings a researcher's rigor to pragmatic engineering, mentoring teams and optimizing workflows to deliver measurable business impact.
10 years of coding experience
15 years of employment as a software developer
Ph.D. Chemistry, Ph.D. Chemistry at Vanderbilt UniversityBachelor of Science Civil Engineering, Bachelor of Science Civil Engineering at Washington University in St. LouisB.A. Physics, B.A. Physics at Greenville College
Github Skills (9)
schema-org10
javas10
schema-design10
schema10
mysql10
java10
data-pipelines9
data-pipeline9
kafka9
Programming languages (3)
Github contributions (5)
zendesk/maxwell
Dec 2015 - Mar 2016
Maxwell's daemon, a mysql-to-json kafka producer
Role in this project:
Back-end Developer
Back-end DeveloperContributions:74 commits, 4 PRs, 27 comments in 3 months
Contributions summary:Kristian primarily focused on enhancing the `maxwell` project's core functionality, specifically concerning update events and schema management. They implemented features to handle old values in updated rows, ensuring data consistency and providing before/after images for filtered rows. Additionally, the user made significant changes to improve the schema management system, including database name configuration and master change handling. These modifications demonstrate a focus on improving data processing and stability of the MySQL-to-Kafka producer.
to-jsonavrosinkmysqldaemon
kristiankaufmann/maxwell
Dec 2015 - Mar 2016
Contributions:1 release, 1 PR, 48 pushes in 3 months
daemonmaxwellscalapusherkafka
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