Professional Experience
Building data-driven solutions and modern web applications with expertise in full-stack development and data science.
Current Role
Data Scientist & Full-Stack Engineer
Lead data scientist and lead full-stack engineer, covering everything from AI agent design to Flask APIs, Airflow pipelines, and frontend builds. Work directly with clients, client success, and the web team across the full product stack.
Key Responsibilities
- Leading full-stack development and marketing video construction of the Audience Architect, an agentic addition to the Audience Builder CDP
- Built a Gemini 2.5 Flash sentiment-scoring pipeline for Kansas State Foundation contact report analysis
- Converted a static RBAC file system into a Python-managed Postgres system, cutting access-control changes from 24 hours to under 5 minutes
- Led modeling and product deployment over 9 months for the Seattle Mariners, LSU Tiger Athletic Foundation, Charlotte Hornets, Winnipeg Blue Bombers, Kansas State Foundation, and Nashville SC
Technologies Used
Previous Experience
Data Scientist & Front-End Engineer
Self-taught React and TypeScript to take on lead frontend development, then balanced that with Figma mockups and predictive modeling work across CDP product and client projects.
Key Achievements
- Built the published-list framework for the Audience Builder CDP, letting 8+ clients share marketing lists across their organizations with non-obstructing web-worker auto-refreshes and rehydration validation
- Refactored a 3+ year-old, 4.5K-line React context into 1K lines of clean Redux, keeping the mask-based filtering system intact with full unit coverage and rollback safety — eliminated 99% of breaking frontend bugs
- Coordinated with gift officers and leadership on product construction and model deployments for the University of Arizona Foundation, leading to a long-term partnership
Data Scientist
Modeler and data engineer focused on building Hierarchical Bayesian Logistic Regression models that gave clients explainable, coefficient-based predictions for lead scoring, pipeline management, and churn prevention.
Key Achievements
- Assisted the frontend team with product backlog triage after a month-long course in React and TypeScript
- Trained and deployed HBLR models for the Ottawa Redblacks and Houston Dynamo while finishing 18 hours of coursework, improving win rates by 7% and cutting cycle times by ~20 days
- Developed filtering-table specs for the Audience Builder CDP — type, column name, and value constraints — for nightly Airflow DAG runs
- Added 50+ unit tests across three in-house R packages, reducing errors in the model parsing workflow, feature evaluations, and JSON deployments to GCP for the Java-based scoring API
Data Analytics Intern
Analytics resource for the mobile app team. Used SQL, Tableau, and Splunk to surface user sentiment, daily login patterns, and in-app flow data for product and marketing decisions.
Key Achievements
- Queried and analyzed large datasets using SQL to generate insights for product and marketing stakeholders
- Created live, detailed Tableau dashboards for Frost product owners, enabling real-time monitoring of feature adoption and usage across thousands of users
- Developed custom Splunk dashboards to surface consumer trends and behavioral patterns on the Frost Bank mobile app, informing roadmap decisions and UX improvements
Data Analytics Intern
Standalone analyst for the news team. Monitored web traffic, built Tableau dashboards that got published directly in digital articles, and scraped public datasets for editorial use.
Key Achievements
- Created Tableau visualizations for digital publications
- Used Python to develop regressions and neural networks to optimize company performance
- Provided feedback on news reports and general system operations
- Scraped and formatted political contribution data from the Texas Ethics Commission for digital publications
- Utilized Dash, Flask, HTML, and Python to develop an adaptable dashboard application
Projects & Articles
A collection of personal projects and technical articles showcasing expertise in full-stack development, AI/ML, and data science.
Audience Architect
Audience Architect
ActiveAn agentic enhancement to PILYTIX's Audience Builder CDP. A LangGraph-powered AI agent that turns natural-language requests into targeted audience segments.
SirenSpec
SirenSpec
ActiveAn open-source, YAML-first workflow orchestration tool for LLMs, built in Python. Targets the middle ground between low-code tools like n8n and highly technical frameworks like LangChain.
College Football Player Fit Summarizer
College Football Player Fit Summarizer
ActiveA full-stack AI system that ingests scraped recruiting data and evaluates player-to-program fit using local LLM inference and structured schemas.
Portfolio Website with Swishter AI
Portfolio Website with Swishter AI
ActiveA modern, responsive portfolio website built with Next.js 15 featuring an intelligent AI assistant named Swishter. Combines clean design with context-aware AI chat for professional inquiries and business communication.
AI Agent Learning
AI Agent Learning
Active LearningA learning repository focused on building AI agents, exploring modern AI/ML techniques and agent-based systems.
NBA Opening Week Predictions: Applying Julia's Machine Learning to Sports
NBA Opening Week Predictions: Applying Julia's Machine Learning to Sports
PublishedTechnical article exploring NBA game predictions using Julia programming language and machine learning. Applied logistic regression to predict outcomes for 25 games in the 2020-2021 NBA opening week.
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Interactive Demos
End-to-end prototypes combining data pipelines, model inference, and production-style UIs.
College Football Player Fit Summarizer
Full-stack system that scrapes recruiting data and performs model-driven player-to-program fit evaluation through an interactive UI. Requests are sent to a FastAPI backend, player data is scraped from 247Sports using Playwright, and the results are summarized and structured via Gemma4:31b on Ollama.
College Player Fit Evaluation
Please provide any college football player and select a team to evaluate how well they would fit within that program using AI.
Beyond the Code
Life's best moments happen away from the screen. Here's a glimpse into the people, places, and passions that keep me grounded and inspired.
Best day ever! Marrying Amelia in 2023 was just the beginning of our adventure together. She somehow manages to put up with my coding marathons and still brings me coffee at 2 AM.
Meet Swish, my Bernedoodle and self-appointed Chief Debugging Officer. He has zero coding skills but somehow always knows when I need a walk break. Those puppy eyes are dangerously effective at ending late-night coding sessions.
Born and raised in Austin, where breakfast tacos are a food group and "Keep Austin Weird" isn't just a slogan. This city taught me that the best solutions often come from the most unexpected places.
Football season is the best season for me - Texas Longhorns for college, Atlanta Falcons for NFL. Yes, I chose pain with the Falcons, but loyalty runs deep. Hook 'em Horns and Rise Up, always!
Trinity University, Class of 2022. Four years of discovering that data tells stories, technology solves problems, and sometimes the best insights come from combining business and sports analytics in unexpected ways.
Swishter
Ask me about Tristan's experience
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