Resume

Gauntlet AI | Remote + Austin, TX

• Use AI first engineering principles to rapidly learn new technologies and build prototype projects over 1 week per project
• Campaign Composer: AI-powered political campaign message composition platform with real-time collaboration and analytics
• CritChat: Mobile TTRPG social platform with AI-powered character interactions and smart group matching
• Glyph: AI-powered native macOS knowledge graph explorer for research analysis and learning plan generation
• Spool: AI-powered personalized learning management system with voice-driven discovery and adaptive assessment
• Echo Sigil: Cooperative 2D puzzle-adventure game with asymmetric magic systems built in Godot
• Knowledge Curator: AI-powered knowledge management and curation platform

Independent | Remote

• Provided consultations for start-up founders
• Maintained learning and growth as AI began rapidly advancing due to LLM progress

Echo Mind AI | Remote

• Wrote data collection algorithm in a health tech start-up using Python, OpenCV, and Linux, to collect business critical data to power the POC for the business.
• Designed and finished proof of concept app and presentations using Java, XML, Android Studios, and Jupyter Notebooks to demonstrate product and business feasibility in sales and investor pitches.
• Built and collaborated on backend and frontend web application features and unit tests using an Agile methodology, Django, ReportLab, HTML, and CSS to build an ultrasound scan submission portal for telesonography use by 10 clients.
• Caught and corrected significant design and data architecture errors by rethinking backend variables and go to market strategy, preventing a complete rewrite of web application.
• Created ML generator to create Convolutional Neural Networks using Python, Jupyter, SKLearn, OpenCV, and Tensorflow to rapidly generate business critical models for analysis.

Messner Reeves LLP | Remote

• Analyzed more than 6,000 billing entries using Python, Pandas, and Jupyter to identify and correct key billing mistakes that led to adjustments being made.
• Built a ML model using XGBoost, Natural Language Processing, and Python, predicting $840,000 worth of adjusted bills over a quarter.

Use survey data to identify the optimal location for a water intervention in developing countries.

• Engineered and cleaned data from 3 sources using Python and Jupyter allowing for core model creation and computations.
• Wrote, tested, and debugged programs in Python to create a program that provided core functionality of identifying optimal water intervention from data.

Built a custom machine learning algorithm to predict the results of the NCAA March Madness tournament.

• Built a web-scraper to scrape data from kenpom.com using Python, Jupyter, and BeautifulSoup to collect 6 years of March Madness results and game data.
• Analyzed data and built visualizations using Python, Jupyter, Seaborn and Matplotlib to visualize and understand core metrics in data for developing the custom model.
• Developed a custom ML model to predict the winning team in a basketball game using statistics, SVMs, XGBoost, and Linear Regression to achieve final project outcome.

Build a simple command line program using statistical probabilities to choose the most probable word in a game of Wordle.

• Built a command line program using Python to calculate the most probable word in Wordle.

EMAI