About James Boggs

I’m James Boggs, a Quantitative & Machine Learning Engineer based in Delray Beach, Florida. I design and deploy production-grade quantitative systems that combine econometrics, statistical modeling, and modern machine learning.

My work focuses on building real, running systems—not static notebooks. These systems power forecasting, pricing, risk analysis, and decision-making workflows through clean APIs and interactive dashboards.

What I Build

I specialize in end-to-end quantitative model platforms, including:

• PyTorch-based forecasting and risk models
• Monte Carlo simulation engines
• Volatility and regime modeling frameworks
• Sentiment and NLP pipelines
• FastAPI services optimized for real-time inference
• Distributed and asynchronous compute systems

Each model is deployed as a standalone service, designed to scale independently and integrate cleanly with front-end analytics.

Technical Perspective

With a background in economics, I approach machine learning with an emphasis on structure, assumptions, and measurable outcomes. I treat ML as an engineering discipline—prioritizing reliability, performance, and interpretability.

Why This Site Exists

This site functions as a live technical portfolio. It replaces static résumés and generic profiles with working systems that demonstrate how I design, build, and deploy quantitative infrastructure.

You can explore live model services and dashboards directly from the homepage or view location-specific context on the Florida page.

Location

I am based in Delray Beach, Florida and work primarily on remote quantitative and machine learning engineering projects involving forecasting, pricing, and applied AI systems.

James Boggs
Quantitative & Machine Learning Engineer
Delray Beach, Florida