About

I recieved my B.S. in Computer Science at Colorado State University, and found that data science fascinated me while taking capstone courses in Machine Learning and Distributed Computing. I trained ML models to detect anomolies in network traffic, and ran data analysis on a Spark cluster to find insights on the current job market. Looking to explore the country and develop my professional expereience, I moved to Philadelphia to start working for Lockheed Martin after graduation. While working at Lockheed for three years, I led many different projects including Data Engineering, ML Engineering, and Systems Engineering. While working, I invested heavily in continuous learning. I began a masters program in Machine Learning at Georgia Tech and recieved a Data Science Apprenticeship Certificate from the Department of Labor. Looking to focus my work on Data Science, I accepted a Data Engineering position at Booz Allen Hamilton in San Diego, the leading contributor to AI solutions to the federal government.

Moving forward I am excited to keep developing and learning as an data scientist, while I also work on building a website, and explore the world of cybersecurity and cloud architecture.

Projects

Trading Stocks with AI

'Traded' historical stock data based on many different stock signals using a Q-Learning algorithm (Reinforcement Learning).

GitHub.

Predicting the Housing Market

With how crazy the housing prices have been lately, I was curious to see the correlations between housing prices and other economic features. I also trained an ARIMA model to predict where prices will go next.

GitHub.

BMI value prediction

Predicted BMI values using a linear regression model using only the Python Standard Library

GitHub.

Contact

Elements

i = 0;

while (!deck.isInOrder()) {
    print 'Iteration ' + i;
    deck.shuffle();
    i++;
}

print 'It took ' + i + ' iterations to sort the deck.';