Jordan Green

Product-minded developer exploring the possibilities of technology and AI.

About Me

Technical background. Product & software development experience. Never-ending curiousity.

I love using my skills and passions to explore cool ideas and solve interesting problems. From integrating a custom Eren Jaeger AI agent into a virtual sandbox to trying to figure out how to make it easier for people in the Bay Area to find community, I find myself being captivated by a wide variety of areas.

When I'm not coding, you can find me hanging out with friends, reading a murder mystery, or having a conversation about the future of AI (among other things).

Technical Skills

Python

Machine Learning

Sci-kit Learn

Hugging Face

PyTorch

Pandas

Git

SQL

Cursor

API Integration

Product Skills

Product Development

User Research

Rapid Prototyping

Market Analysis

Data-driven Decision Making

MVP Development

My Portfolio

Vibe

Building an app to make it easier for college students to connect with other students and meet their people.

Case Study

Rapid Prototyping

Flutter

Product Development

Product Strategy

Bay Area Discord Discovery

A simple web app for finding discord servers in the Bay Area (vibe coded in a day), and my journey building it (longer than a day).

Case Study

Product Development

User Research

Rapid Prototyping

AI QuickBooks Assistant

An AI powered web application that allows users to use natural language to access their QuickBooks data.

Flask

OpenAI API

LangChain

Airbnb Price Predictor

A fine-tuned machine learning model that predicts the price of an Airbnb listing based on its features.

XGBoost

Pytorch

Scikit-learn

High Performance Server/Evaluation

I built a multi-threaded server capable of storing and processing images. I also extracted and analyzed and visualized data from the server using Python

Next.js

Framer Motion

Tailwind CSS

Game Odds Calculator

Building on an existing application, I refined the probability calculations to make it more accurate using Markov Models.

JavaScript

Markov Models

AT Protocol Jetstream Analytics Dashboard

I built a analytics dashboard for users to view the amount of traffic on the AT Protocol.

ETL Pipeline

Data Visualization

Liar's Dice Strategy

Using the techniques presented in Marc Lanctot and Todd W. Neller's paper on Counterfactual Regret, I built a model that calculated the game theoretical optimal strategy for Liar's Dice

Java

Counterfactual Regret

Reinforcement Learning

Get In Touch

I'm currently looking for opportunities to work on projects that challenge me and help me grow. Feel free to reach out to me if you'd like to chat!

Contact Me