Kevin Leahy is a Senior Data Scientist and Software Engineer based in Sydney with a decade of experience building production ML systems across energy, finance, sports, and mobility. He holds a PhD applying machine learning to wind turbine health and has a track record of turning noisy, real-world time-series into deployed fault-prediction and decisioning systems. Kevin has led end-to-end model development and MLOps—shipping models that now automate credit risk decisions for multi-billion-dollar portfolios and optimise distributed renewable energy at SwitchDin. He blends research-grade rigor (peer-reviewed publications, a reusable WTPHM data package) with pragmatic cloud-native engineering across AWS and Azure. Comfortable translating complex analytics to non-technical stakeholders, he also mentors teams and improves data science practices to scale impact. An unusual strength is his ability to move from field-level energy audits to deployed ML pipelines, bridging domain expertise and production software delivery.
10 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at University of California, Berkeley
Doctor of Philosophy - PhD Engineering, Doctor of Philosophy - PhD Engineering at University College Cork
Wind Turbine Fault Detection. Newer version @ https://github.com/lkev/wtphm
Contributions:83 commits, 2 PRs, 43 pushes in 6 years 3 months
version-newerfaultwindfault-detectionnewer
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Kevin Leahy - Senior Data Scientist Software Engineer