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 with 3+ years of experience designing and shipping production ML, analytics, and security automation systems in Go and Python. I combine software engineering with mathematics, statistics, economics, and applied research to build end-to-end products spanning streaming ingestion, model orchestration, agentic workflows, APIs, data infrastructure, and analyst-facing interfaces.
At Arancia, my current work includes autonomous SOC decisioning, anomaly detection, probabilistic modeling, and high-volume enterprise event analytics. At Brock University, I'm pursuing two undergraduate theses in Bayesian network structure learning and cybercrime economics.
Outside of work, I contribute to open-source projects, compete in programming and chess events, lead the Brock Bouldering and Climbing Club, and stay active in track and field.
Arancia · Remote / Ontario
Calian IT & Cyber · Ontario
Under review at Decision Analysis
A decision-analytic framework for allocating a fixed alert budget across complementary behavioral detectors, accounting for shared coverage, harm, and uncertainty.
Read manuscript (PDF) 2026Supervised by Dr. Taylor Wright
An empirical study of cybersecurity-related 8-K filings before and after the SEC's Item 1.05 rule, examining reporting intensity, disclosure timing, content, and filing-date market responses.
Read paper 2026Supervised by Dr. Pouria Ramazi
Conducted research under Dr. Pouria Ramazi on efficient search, scoring, and interpretable probabilistic modeling, translating theoretical methods into reusable algorithms and experiments. This work directly informs the bngo open-source library.
2025 — 2026Rec League Sports Analytics & Predictions
Vercel-ready analytics dashboard and Go API that ingests Brodie League public statistics to project team moneylines and player stat props using exponentially weighted and rolling-average models. Includes a filterable betting board, model comparison and tuning, Postgres caching, and automated data synchronization. Walk-forward backtests achieved 69.0% moneyline accuracy and a 0.204 Brier score across 87 Niagara Spring 2026 games.
Bayesian Network Library
Go package for Bayesian networks supporting structure learning, parameter learning, probabilistic inference, simulation, prediction, and mixed discrete-continuous modeling. Connected to ongoing undergraduate research in Bayesian-network structure learning.
Sports Data Scraping
Python scraper that collects Trackie U SPORTS results and computes Brock University athlete personal bests across recent seasons. Produces analysis-ready datasets with normalized performances, meet metadata, and derived dates for downstream sports analytics.
Regression Modeling
Regression-based geotargeting analysis for the Niagara Falls Canada Hotels Association to identify stronger advertising regions and improve return on advertising spend. Translated model findings into practical regional targeting recommendations for a non-technical stakeholder audience.
St. Catharines, Ontario
Honours BSc in Mathematics and Economics
Concentration in Statistics • Minor in Computer Science • 3.8 GPA
Subject averages: Mathematics A+ • Statistics A • Computer Science A • Economics A+
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
Captain, Korah C&VS Track and Field Team & Wrestling Team
ICPC North America East (2023, 2024)
Canadian University Chess Championship (2023, 2024)
Organized the Mind Over Matter chess tournament, raising over $1,000 for the Child and Adolescent Mental Health Unit at Sault Area Hospital.
Maintain public repositories spanning Bayesian networks, Terraform tooling, sports-data scraping, and data infrastructure in Go, Python, and Java.
I'm always open to interesting conversations about machine learning, quantitative research, or new opportunities. Feel free to reach out.