I'm a Software Engineer & Data Scientist with a BSc in Computer Science from Brooklyn College and currently pursuing an MS in Data Science at CUNY. I am passionate about leveraging data and technology to solve real-world problems, with expertise in software engineering, and machine learning My Portfolio

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• Description: Built an open-source assistant that helps developers understand GitHub repositories by providing intelligent responses to queries about contribution guidelines, setup, and documentation using NVIDIA NIMs' embedding and LLM capabilities.
• Tech Stack: NVIDIA NIMs (nv-embedqa-e5-v5, llama3-70b-instruct), Pinecone Vector DB, Flask, Next.js, Material UI

• Description: Implemented a dynamic web application in Next.js and Material-UI that generates flashcards using Google's Gemini API based on user-provided topics, enhancing learning efficiency.
• Tech Stack: Next.js, Vercel, Firebase, Google Gemini

• Description: An AI-powered chatbot designed for real estate customer support. Utilizes Google’s Gemini for natural language understanding and is hosted on AWS EC2. The frontend is built with Next.js and styled using Material UI for a modern, responsive user interface.
• Tech Stack: Google Gemini, AWS EC2, Next.js, Material UI

• Description: A web application designed to help users keep track of their pantry items. Users can add, edit, and delete items, as well as search for specific items in their pantry. The application provides a user-friendly interface for managing pantry inventory efficiently.
• Tech Stack: Next.js, Firebase, Material-UI, Vercel

• Description: A machine learning project focused on classifying types of clouds from satellite images. This project explores convolutional neural networks for image processing and classification, highlighting my deep learning and neural network skills.
• Tech Stack: Python, PyTorch, Matplotlib

• Description: This project involves a comprehensive analysis of presidential speeches using natural language processing and network analysis techniques. Leveraged NLTK and NetworkX to perform sentiment analysis and construct a network graph of co-occurring keywords. This project demonstrates my ability to extract, process, and analyze textual data, uncovering key themes and relationships within the speeches.
• Tech Stack: Python, NLTK, NetworkX, Matplotlib, Pandas

• Description: A Kaggle competition project predicting house prices based on various features. Implemented multiple regression models and feature engineering techniques to improve prediction accuracy.
• Tech Stack: Python, Scikit-learn, Pandas

• Description: An exploratory data analysis project on property sales data to uncover trends and insights. Includes data cleaning, visualization, and statistical analysis.
• Tech Stack: R, ggplot2, dplyr

• Description: Developed a web application to allow doctors to CRUD structured radiology reports as an assessment of x-ray images for patients with COVID-19. The project significantly increased efficiency and reduced integration time for frontend and backend components.
• Tech Stack: MERN (MongoDB, Express.js, React, Node.js)

• Software Engineer Intern at ezCater (Jun 2023 – Nov 2023):

  • Deployed UI modifications using feature flags for A/B testing, contributing to a 7.66% increase in bookings per user, 8.25% increase in revenue per user, and a $1.7M increase in annual revenue.
  • Revamped the "Caterers Near Me" page using Ruby on Rails, resulting in a 6% increase in paid search conversions, a 3% rise in average order value, and a +12.55% lift in conversion rates from paid search, driving significant business impact.

• Hack.Diversity Fellow (Dec 2022 – Aug 2023):

  • Selected among the final 15 out of 300 candidates for the fellowship.
  • Engaged in projects integrating software engineering with NYC’s key economic sectors, enhancing professional development and collaborative skills.

• LinkedIn: Tilon Bobb
• GitHub: Kingtilon1
• Email: [email protected]

• Django Web Framework by Coursera
• Introduction to Databases for Back-End Development by Coursera
• Microsoft's 30-Day Azure Machine Learning Challenge

• Basketball: Playing and following the latest games and stats.
• Video Games: Enjoying a wide range of genres, from RPGs to competitive shooters.
• Anime & Manga: Watching and reading various series, exploring different genres and stories.

Feel free to explore my repositories and get in touch!