Open to new opportunities
Data Scientist & Engineer
I’m a San Francisco-based data scientist passionate about using data and machine learning to solve meaningful, real-world problems. Outside of modeling and code, you’ll usually find me staying active on the volleyball court, exploring new corners of SF, or planning my next travel adventure. Above all, I’m grounded by quality time with family and great friends, always looking for good food and new experiences along the way.
Based in
San Francisco, CA
About me
I build thoughtful, well-tested software and translate complex research into work people can actually use.
I am a data scientist and machine learning practitioner focused on turning complex, high-dimensional data into robust predictive models and real-world systems. With a strong foundation spanning classical machine learning, deep learning architectures, and scalable MLOps, I build pipelines designed not just for high benchmark accuracy, but for reliability, low-latency deployment, and measurable impact.
My work bridges technical rigor with high-stakes problem-solving—from developing time-series models that forecast critical real-time indicators to analyzing millions of records to uncover systemic patterns and drive algorithmic accountability. Whether engineering end-to-end data pipelines on cloud infrastructure, fine-tuning model architectures, or designing automated monitoring to prevent data drift, I focus on building transparent, reproducible, and production-ready solutions.
Currently, I am looking to collaborate on high-impact machine learning and data engineering initiatives. If you are building data-driven systems that require both technical precision and thoughtful execution, let’s connect.
Résumé
The roles that shaped how I work, in reverse chronological order.
Oct 2025 — June 2026
American Civil Liberties Union (ACLU) of Northern California · San Francisco, CA
Built machine learning systems for algorithmic accountability work — real-time LLM agents, large-scale public records analysis, and anomaly detection used to support legal action and city policy.
Dec 2022 — July 2025
Stanlee Gatti Designs · San Francisco, CA
Ran on-site production and acted as the technical point of contact for high-profile events, coordinating vendors, logistics, and spatial planning under live deadlines.
Nov 2020 — Sep 2022
McMillan Electric · San Francisco, CA
Managed technical project delivery and network infrastructure assessments for high-rise commercial and residential properties across the San Francisco Bay Area, deploying telemetry-driven risk assessment models to diagnose connectivity vulnerabilities, remediate outages, and ensure high-availability network performance.
Projects
A selection of work with the context behind it — what the problem was, what I did, and how it turned out.
Apparel resale price prediction, trained on 500,000 listings.
A web application that estimates what a piece of apparel will resell for. An XGBoost regression pipeline trained on 500,000 listings predicts resale value to a $30.90 mean absolute error, and a PyTorch convolutional neural network handles multi-class visual classification so new listings can be categorized automatically at ingestion.
A multi-agent coach that plans training around the time you actually have.
A personalized multi-agent workflow that uses LLM reasoning, prompt engineering, and context-aware orchestration to evaluate a user's goals against their changing circumstances. An optimization routine queries the Google Calendar API to ingest schedule data and plan sessions autonomously in whatever blocks are open.
Presentations
Work I've shared with an audience — conference talks, invited seminars, and poster sessions.
University of San Francisco, CA
Following the federal class-action settlement in Mathis v. County of Siskiyou—which addressed significant racial profiling patterns in traffic stops—independent monitoring required extensive auditing of traffic stop interactions. Manually reviewing hundreds of hours of body-worn camera (BWC) footage is time- and labor-intensive. This project implements an automated, privacy-preserving transcription and legal audit pipeline designed to scale oversight and accountability.
ACLU of Northern California - Video Call Presentation
An analysis of San Jose Automated License Plate Reader data to identify patterns and anomalies.
Education
Degrees and the coursework behind them.
Jul 2025 — Jul 2026
University of San Francisco · San Francisco, CA
Selected coursework
Aug 2014 — Dec 2017
Chapman University · Orange, CA
Selected coursework
Contact
I'm looking to collaborate on high-impact machine learning and data engineering work. Email is the fastest way to reach me, and LinkedIn works just as well.