Machine Learning Engineer
Building production-grade ML systems, probabilistic models, and data products at the intersection of software engineering and quantitative research.
I'm a Machine Learning Engineer currently building production-grade ML and analytics services at Arancia, working across anomaly detection, user-behavior analytics, and high-volume enterprise event data systems.
My academic foundation spans mathematics, economics, statistics, and computer science at Brock University, where I maintain strong grades across stochastic processes, Bayesian methods, econometrics, and AI coursework. I'm pursuing two undergraduate theses, one in Bayesian network structure learning and another in cybercrime economics.
I combine software engineering discipline (Go, Python, Terraform, Docker) with quantitative modeling to build systems that are both rigorous and deployable. Outside of work, I'm a hobby enthusiast, doing various things such as making open-source software contributions, doing standup comedy, or running a local rock climbing club.
Arancia
Calian IT & Cyber
Bayesian Network Library
Go package for Bayesian networks supporting structure learning, parameter learning, probabilistic inference, simulation, and prediction. Focused on interpretable modeling and uncertainty-aware reasoning.
Sports Data Scraping
Python scraper collecting Trackie U SPORTS results and computing Brock University athlete personal bests. Exports athlete-level event data to CSV with normalized performances and meet metadata.
Infrastructure & APIs
Contributed to a Terraform provider that executes HTTP requests and stores responses in Terraform state. Strengthened experience with provider development, API integrations, and production-grade Go codebases.
Regression Modeling
Regression-based geotargeting analysis for the Niagara Falls Canada Hotels Association to identify stronger advertising regions and improve ROI. Delivered an interpretable recommendation framework.
Supervised by Dr. Pouria Ramazi
Conducting research on Bayesian network structure learning, with emphasis on efficient search, scoring, and interpretable probabilistic modeling. This work directly informs the development of the bngo open-source library.
2025 — PresentSupervised by Dr. Taylor Wright
Building empirical datasets and quantitative workflows for cybercrime economics research, covering disclosure impacts, market dynamics, and policy analysis through econometric methods.
2025 — PresentSt. Catharines, Ontario
Honours BSc in Mathematics and Economics
Graduating 2027 • Concentration in Statistics • Minor in Computer Science • 3.7 GPA
Topics in Stochastic Processes and Models, Mathematical Statistics I, Probability, Regression Analysis, Experimental Design, Forecasting Using Time Series Data, Econometrics, Microeconometrics
Artificial Intelligence, Programming for Big Data, Advanced Data Structures, Computer Architecture, Bayesian and Causal Bayesian Networks, Discrete Optimization, Game Theory
President, Brock University Bouldering and Climbing Club
2025 — Present
Brock Badgers Track and Field
ICPC North America East (2023, 2024)
Canadian University Chess Championship (2023, 2024)
Organized the Mind Over Matter chess tournament, raising $1,000+ for the Child and Adolescent Mental Health Unit at Sault Area Hospital.
Public repositories in Bayesian networks, Terraform tooling, sports-data scraping, and data infrastructure.
I'm always open to interesting conversations about machine learning, quantitative research, or new opportunities. Feel free to reach out.