About Me

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Hi! My name is Jacob Foster. I am 24 years old and I am from Katy, Texas. I have earned my BBA in Management Information Systems and my Master of Science from the University of Texas McCombs School of Business. Currently, I am a data engineer at PepsiCo within the Frito-Lay warehousing division, where I work daily with Python, SQL, Microsoft Azure, and enterprise messaging systems. Additionally, I serve as a part-time full-stack engineering consultant for a small financial firm based in Dallas. Outside of work, I enjoy playing almost any sport, especially baseball, and collecting Legos. I am always eager to gain new experiences and learn new things, whether through traveling, work, or impromptu opportunities!

Fun Facts

  • Favorite Team: Houston Astros
  • Favorite Food: Buffalo Chicken Sandwich
  • First Job: Lifeguard
  • Favorite Movie: The Greatest Showman
  • Favorite Animal: Cat

Resume

Projects

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Dallas Restaurant Recommender

Streamlit based AI chatbot application integrating data from Google Places API and OpenAI APIs. Delivers quick, relevant responses in natural text to questions or prompts about restaurants in Dallas. Check out the website by clicking on the link above!

Link to Repo
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Inventory Management Application

Uses Python Flask backend, following Model-View-Controller architecture principles with a React.js frontend. Flask backend connects to MongoDB serverless database for efficient retrieval and storage.

Link to Repo
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Arduino Bat Speed Reader

Bat speed reader based on accelerometer data from an Arduino M5StickC-Plus (written in C++) that commmunicates data over a REST API to a Node.js backend. Results are stored per user in a MongoDB serverless database and a personal record is shown for each user and global leaderboard is displayed for all users using React.js.

Link to Repo
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Austin Bar Recommender

Jupyter Notebook that uses Google reviews of Austin bars to generate recommendations for users based on their input. These are generated using NLP practices such as word embeddings on user input and sentiment and similarity score on existing reviews to generate accurate suggestions. The application is based in Python and uses the spaCy, VADERSentiment, and pandas libraries.

Link to Repo
Contact Me