Derrek Warren Gass has a Bachelor of Science in Computer Science from California State University, Sacramento with a GPA of 3.26. He has skills in languages like Python, C++, Java, JavaScript, and frameworks like React, Express, Node. Gass has work experience as an intern at Hi.Delivery where he created UI components and as a sales associate at Green Heart Club. Recent projects include developing a web app for Flashpoint Learning using React, Node, and AWS and creating interactive data visualizations with D3.

1. Derrek Warren Gass
(916) 690-7701 | dwgass@gmail.com | linkedin.com/in/derrekgass | github.com/lazertooth
Education:
California State University, Sacramento GPA 3.26
Bachelor of Science in Computer Science Fall 2019
Skills:
● Languages: Python, C/C++, Java, JavaScript, Rust, Ruby, MySQL, Postgres, HTML, CSS, Sass, TypeScript
● Frameworks & Libraries: React.js, Express.js, Node.js, D3.js, TensorFlow, Bootstrap
● Additional Tools: Git, NPM, Colab, Google Cloud Compute, Spring Boot, AWS, Jupyter Lab, Selenium
Work Experience:
Hi.Delivery Apr 2018 – Aug 2018
Intern
● Worked with a small, 2-man startup to develop a PaaS to track online sales, inventory, delivery, and invoicing for
local businesses with a shoestring budget.
● Created reusable, responsive UI components with unit and integration testing.
Green Heart Club July 2016 – Jan 2018
Sales Associate/Dispatch
● Worked in inventory management for a medical supply chain to ensure sufficient support of core business goals
while enhancing customer satisfaction through quality interaction and efficiency.
● Managed sales calls and coordinated the successful dispatch of goods into the hands of our clients.
Recent Projects:
Flashpoint Learning Jan 2019 – Dec 2019
● Working with a team of six other software developers with SCRUM methodology, I managed the front-end
development of a full-stack, progressive web application built with React.js, Node.js, Spring Boot, and deployed
with Amazon Web Services.
● Developed End to End test automation strategies in support of our continuous integration and delivery pipeline.
● Maintained our product backlog and repository, scheduling and assignment of tasks, and arranged bi-monthly
code reviews and client meetings, to render a contract from SRS to shippable product.
Interactive Visualization of State Homelessness Dec 2019
● Implemented a series of interactive widgets with D3.js that visualize different exploratory aspects of the
Department of Housing and Urban Development’s annual Point-In-Time count dataset.
● Data wrangling expediated by leveraging Pandas for batch CSV file conversion.
Time-Series Forecasting of Financial Data with LSTM Nov 2019
● Trained and optimized hyperparameters of a LSTM model to predict financial trends and anomalies in the S&P500.
Image Classification Network Oct 2019
● Trained a Convolutional Neural Network for supervised learning of common objects using the CIFAR-10 dataset, with
an averaged F1 score of 0.73.
● Developed an alternative solution with transfer learning using the VGG16 model, providing a training speedup of 4X.
Network Anomaly Detection Oct 2019
● Used the KDD ‘99 Cup dataset to train a predictive model that detects fraudulent network connections.
● Achieved a 99.85% accuracy rating with a convolutional neural network built with TensorFlow and Pandas.
Yelp Rating Prediction Sep 2019
● Created a Recurrent Neural Network to predict the Yelp rating of a business using Natural Language Processing and
sentiment analysis, trained on over 1.2 million reviews, with a final RMSE of 0.45.
Asteroids Redux Dec 2018
● A remake of the classic asteroids game, based in Java. I exercised best design practices and synthesized
original audiovisual assets with a simple but elegant theme while employing OOP principles.
Clubs and Activities:
● Member, Associated Computing Machinery Fall 2018 – Present
● Member, Institute of Electrical and ElectronicsEngineers (IEEE) Fall 2018 – Present