Sean Hart
A collection of personal projects and other work.
Sean Hart - Project’s and Links
🚀 Technical Skills: Python, Pandas, SQL, PHP, Flask, C++
📚 Education
- Baruch College (Financial Math) Expected Graduation 2027
- LaGuardia Community College Associates Bachelor’s of Science (Computer Science, GPA: 3.91)
- Flatiron School (Data Science Bootcamp)
- Upright Citizens Brigade (Improv & Comedy Writing)
💵 Finance Projects
Meta Reels Analysis
A quick look at the enourmity of Meta’s revenue from Reels.
Bond Yield Exploration
This project explores U.S. Treasury yields and spreads using data from the FRED API . It starts with a Jupyter Notebook for fetching and visualizing yields, then builds toward a lightweight ETL pipeline and dashboard.
Basic Pattern Backtester
- Ingests stock and ETF ticker symbols
- Implements a basic pattern backtesting workflow
- Generates candlestick charts for selected securities
- Provides a foundation for experimenting with technical analysis strategies
💻 Data Apps
I Was There
A web app that allows users to input a setlist.fm username and fetch attended concerts.
- Runs a YouTube search to find relevant concert videos.
- Utilizes multiple APIs and performs ETL with a Flask backend.
- Built as a single-page React app with a dynamic and intuitive UI.
Logarithms.org
A simple web app that helps math students understand logarithms.
- Uses the ChatGPT API to generate logarithm explanations in plain language.
- Designed for students unfamiliar with logarithmic notation and syntax.
- Built using Flask and React for a clean and responsive experience.
🔐 Cybersecurity Projects
📊 Splunk SIEM - Failed Login Detection
Built a Security Information & Event Management (SIEM) solution using Splunk to monitor and analyze failed login attempts.
- Set up Splunk in Docker to collect and analyze security logs.
- Simulated failed SSH logins and brute-force attacks.
- Created Splunk queries to detect suspicious login activity.
- Automated alerts for repeated failed logins.
📊 Data Science Projects
- Movie Analysis (Exploring trends and patterns in the film industry.)
- King County Home Prices (Predicting home values using machine learning.)
- Customer Churn Prediction (Built a model to analyze and predict customer retention.)
- Twitter Sentiment Analysis (Examining sentiment trends across social media.)
💼 Work Experience
- Esme Greenpoint (Restaurant & Operations Management)
- Songs for Help Podcast (Co-host & Content Creator—Exploring music and pop culture through engaging discussions.)