Nicholas Buhagiar
Staff Machine Learning Engineer at Cash App
Ottawa, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolNicholas Buhagiar is a Staff Machine Learning Engineer with 11 years of experience building data-driven systems across finance, geospatial, transportation, and healthcare domains. He currently leads ML efforts at Cash App / Block, where he designs fraud-detection models, engineers feature pipelines and ML artifact tracking, and runs experiments to harden card-risk controls at scale. Previously he forecasted maritime and airport traffic with tree ensembles, deployed CNNs for critical waveform detection, and helped formalize data-science practices and tooling within engineering teams. Based in Ottawa, he combines strong production ML engineering with stakeholder-facing analytics and dashboarding, enabling product and risk teams to act on insights quickly. Collected experience in ETLs, feature engineering, A/B testing, and operational monitoring underscores a pragmatic focus on turning models into measurable business impact.
11 years of coding experience
6 years of employment as a software developer
Bachelor of Science (BSc), Physics, Bachelor of Science (BSc), Physics at University of Ontario Institute of TechnologyToronto Metropolitan University
English
Github Skills (18)
simulation10
twitter10
linkedin10
monte-carlo10
data-science9
pytorch9
python9
machine-learning9
tensorflow9
deep-learning9
jax8
gephi8
java8
visualization8
opengl7
Programming languages (4)
Github contributions (5)
hashkat/hashkat
Apr 2015 - Oct 2016
#k@ is a dynamic network simulation tool designed to model the growth of and information propagation through an online social network. It is an agent-based, Kinetic Monte Carlo engine capable of simulating online networks such as Facebook, Twitter, LinkedIn, etc.
Contributions:696 commits, 687 pushes, 4 branches in 1 year 5 months
linkedinmonte-carlosimulationtwitter
nbuhagiar/thesis
Sep 2015 - Sep 2016
Contributions:182 pushes, 1 branch in 1 year
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