Ben Horsburgh
Associate Partner Senior Principal ML Engineer
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolBen Horsburgh is an Associate Partner and Senior Principal ML Engineer based in London with eight years of industry experience and a PhD focused on music recommendation systems. He has progressed through technical leadership roles at QuantumBlack, AI by McKinsey, shaping ML strategy and delivery across principal and partner levels since 2019. Ben blends deep research pedigree with hands-on engineering, having led search, recommendation and personalization efforts at Argos and scored production-ready ML at Tesco and SmartFocus. He contributes to open-source causal inference tooling—improving Bayesian Belief Network implementations in the widely used causalnex library—bringing probabilistic reasoning into practical pipelines. Known for translating academic insight into robust enterprise solutions, he pairs model rigor with product-minded deployment and team mentorship. An unexpected strength is his musical training (DipLCM in Classical Guitar), which informs a pattern-oriented, creative approach to problem solving.
9 years of coding experience
10 years of employment as a software developer
Mackie AcademyDoctor of Philosophy (PhD) Integrating Content and Semantic Representations for Music Recommendation, Doctor of Philosophy (PhD) Integrating Content and Semantic Representations for Music Recommendation at Robert Gordon UniversityDipLCM Classical Guitar, DipLCM Classical Guitar at London College of Music
Stackoverflow
563reputation
34kreached
43answers
0questions
Github Skills (16)
bayesian-network10
causal10
machine-learning10
bayesian10
causality10
python10
bayesian-inference10
causal-inference10
data-science9
pandas9
documentation8
algorithm6
apache-spark6
recommendation-engine6
hadoop6
Programming languages (3)
Github contributions (5)
mckinsey/causalnex
Jan 2020 - May 2020
A Python library that helps data scientists to infer causation rather than observing correlation.
Role in this project:
Data Scientist
Data ScientistContributions:8 releases, 25 commits, 9 PRs in 4 months
Contributions summary:Ben's contributions primarily involved modifying and updating the `causalnex/ebaybbn/bbn.py` file, indicating a focus on the Bayesian Belief Network (BBN) implementation. Their commits include initial setup for version 0.4.0, release of version 0.4.0, merging of master and develop branches, and hotfixes related to documentation and links within the project. The user also addressed issues related to fitting CPDs with missing states and contributed to plotting with PyGraphViz, enhancing the library's functionality.
pythoncausal-inferencecausal-modelscausal-networksbayesian-networks
benhorsburgh/pyslab
Feb 2021 - Aug 2021
Contributions:21 pushes, 1 branch in 6 months
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