I work on problems where data, software, and consequential decisions meet.

I'm an economist by training, with an MA in Economics from the University of Toronto. My work has ranged from institutional real estate finance and investment to econometrics, data science, and software. The common thread is applied decision-making: using data, models, and judgment to understand complex problems and decide what to do.

I spent three years in institutional real estate investment and development, working on underwriting, financing, capital allocation, and strategic decisions across a billion-dollar development program. Today, I'm a replicator for the Journal of Political Economy, working across empirical research pipelines and computational workflows.

I also contribute to open-source econometrics and build projects across machine learning, quantitative research, and software.

Much of my work comes back to one question: given the evidence, what should we actually do?

Contact

The fastest way to reach me is email. I'm also on LinkedIn and GitHub.

Work

  • Senior Financial Analyst, Chard

    2022–2025 · Institutional real estate finance

    Worked across underwriting, capital allocation, debt financing, forecasting, and portfolio decisions for a $1B real estate development program. I also built data and market-intelligence systems to make those decisions faster and more repeatable.

  • Data Scientist, Sciences Po

    2024 · London bus networks

    Built a geospatial dataset from more than 50 million GPS observations to study how London's bus network operates, including efficiency, asset utilization, spatial competition, and market power.

  • Replicator, Journal of Political Economy

    2025–Present · Empirical research

    Reproduce and audit empirical research across R, Stata, Python, Julia, and shell, checking statistical methods, outputs, dependencies, and whether the results can actually be reproduced.

Projects

  • Marketplace simulation

    Production-style ML systems demo

    Simulated orders and couriers with matching, routing, ETA estimation, batching, experimentation, monitoring, and CI/CD.

  • Mars Water Search

    Agents & decision-making · Sundai Club research prototype

    Four AI rovers, limited budgets, one discovery prize. An experiment in search, incentives, and collaboration.

  • Open source

    PyFixest · RovingBandit

    Contributions to econometric inference tooling and multi-armed bandit algorithms.

Research

Contact

The fastest way to reach me is email. I'm also on LinkedIn and GitHub.