Ask who I am, what is in this portfolio, how projects connect, or what evidence backs any claim. I pull from the site docs.
Drew Boynton
Software/ML Engineer
I build production-focused ML and data products end to end, from feature pipelines and model inference to APIs, frontend delivery, and automated monitoring.
Python
TypeScript
Next.js
React
Supabase
BigQuery
Gemini
Tailwind
Selected Work
Flagship Systems
End-to-end systems with measurable outcomes, live interfaces, and automated data pipelines.
Sports Edge: Multi-League Sports Modeling 🏈
Production sports modeling stack covering NBA, NFL, MLB, PGA, CBB, and World Cup. BigQuery holds source-of-truth data; Python pipelines score games and sync to Supabase for the ops dashboard and this portfolio. Compare model spreads and win probabilities against sportsbook lines to surface edges.
- -Ops dashboard at sports-edge.drewboynton.com
- -BigQuery source of truth + Supabase serving layer
- -Automated daily/weekly prediction pipeline across six leagues
PythonScikit-learnLightGBMSupabaseNext.jsSports Analytics
Telemetry stats on the laptop — click through for the pipeline story or open the ops dashboard for live predictions.
LLM Advisor: Agentic Trading System 🤖
Autonomous trading agent that uses Gemini to analyze market context, adjust mean-reversion thresholds, and execute paper options with guardrails. Premarket bias from ICTML folds into one trading-advisor story.
- -Paper options on 7–14 DTE with MR/TC setup types
- -Hybrid ML + LLM validation funnel
- -Risk controls tied to execution rules
PythonGemini APIAlpacaPandasBacktesting
Paper-trading ops dashboard at llm-advisor.drewboynton.com — click the laptop for the deep dive.
MatchPoint: AI Job Matcher 🎯
AI job matcher: daily ingestion from 70 Greenhouse boards, two-stage embedding + LLM matching against your resume.
- -5,867 live jobs corpus refreshed daily
- -8-dimension LLM fit scoring with grounded highlights
- -Sub-10ms vector search via precomputed embedding matrix
React 19FastAPIOpenAITursoSupabaseVercel
Click the laptop for architecture and matching details, or try the live app.
NBA Hall of Fame Predictor 🏀
Interactive machine learning model that estimates NBA players' Hall of Fame chances from career production, peak impact, longevity, and award history. Features real-time player lookup and detailed prediction analysis using XGBoost trained on 5,250+ players since 1976. Try entering any NBA player name!
- -5,250+ historical player careers
- -Interactive probability search for any player
- -Feature-level model reasoning on each prediction
PythonXGBoostNext.jsTypeScriptBasketball Analytics
Search from 5,250+ NBA players • Click the screen above to see behind-the-scenes
My Personal Portfolio Website
What started as a portfolio site grew into its own project - TypeScript and Next.js up front, Supabase and BigQuery underneath. Flagship projects use stats-screen laptop displays and link out to live ops dashboards; includes a Gemini chatbot (Vertex AI, RAG over this site's content).
TypeScriptNext.jsReactTailwindSupabaseBigQueryGemini / Vertex AIRAG
Additional Projects
Smaller builds and experiments that highlight breadth across data science, frontend, and algorithmic thinking.
Mancala AI with Game Theory (Try to beat the AI!)
Intelligent Mancala game implementing minimax algorithm with alpha-beta pruning optimization. The AI evaluates game states 5 moves ahead, achieving 70-80% win rate against random opponents with 10x performance improvement through pruning. Features Monte Carlo simulation analysis for strategic validation.
Minimax AlgorithmAlpha-Beta PruningGame Theory
Advanced Data Cluster Sorting
Project for my Advanced Data Science class. This project was a individual effort to sort data into clusters based on their similarity. We used a variety of data structures and algorithms to achieve this.
PythonPandasGaussian Mixture Models
CU Boulder Police Department Heatmap
A simple heatmap of the CU Boulder Police Department data and its most common location occurrences.
ReactNext.jsTypeScriptTailwind CSS
Simple Fitness (Tracking App!)
A native iOS app for tracking strength training and cardio workouts. Built with Swift and CoreData, this was a fun introduction to iOS development and its ecosystem compatibility. This was more a fun project just to learn more about iOS development and its language capabilities.
XcodeSwiftCoreData
