Portfolio

Developed an automated data pipeline for a university art center to process organic social post metrics, paid social campaign data, website performance, and email campaign data. Using scheduled Python API scripts, along with Google Cloud scheduling and database functionality, the pipeline provides live data to a Looker Studio dashboard for the client.

This solution replaced a cumbersome manual data collection and reporting process, enabling the center to visualize data in ways that were previously unavailable.

Developed an automated data pipeline for a major university health system to process marketing and call data from multiple platform API sources. The Python-based pipeline stores and aggregates data in a SQL database and connects to a Tableau analytics dashboard for marketing executives.

This automation replaced a manual monthly data export and upload process, streamlining reporting and improving overall data accuracy. It reduced the data refresh time from approximately 10 hours to a five-minute automated script run each month.

Developed a containerized application and automated daily reporting process leveraging AI technology to analyze and categorize over 2,000 social media posts each day based on message content.

This automation replaced a time-consuming manual process that required two hours per day, significantly improving efficiency and accuracy, while reducing the margin for human error. The final categorized data is summarized in a structured Google Sheet for simplicity.

Zone In Columbus was an initiative to modernize Columbus’s zoning code while empowering the community to shape the future of city development.

Developed an automated data pipeline that transformed unstructured survey responses from MongoDB into Google BigQuery and designed a live visual dashboard for the Zone In team and the public to analyze survey results in real time.

The dashboard was featured at the Zone In public gallery, where individuals could learn more about the zoning code proposal in an interactive environment.

The Greater Region Mobility Initiative was a project in the Miami Valley region of Ohio aimed at improving transportation services and reducing accessibility barriers.

As part of the initiative, a public survey was developed to gather insights on community transportation needs. This involved designing the question set, implementing the survey on a digital platform, and using QR code and link tracking to monitor distribution and engagement.

A real-time dashboard was created to display public survey results, including data on survey reach, participant demographics, and transportation service utilization and challenges. The publicly-accessible dashboard provided key insights that directly informed the region’s latest transportation plan.

Create and manage content on my baseball YouTube channel, which features playoff and monthly highlight compilations, video essays, and mini-movie edits.

The channel has currently amassed over 290,000 subscribers and over 350 million total views.

Developed a Flask-based web app that allows users to log in with their Spotify credentials and explore their listening habits. The app displays users' most-played artists and tracks, along with insights into track popularity, release dates, and artist follower counts.

InTune integrates with the Spotify API to fetch real-time listening data.

Currently developing a Python-based web application utilizing Tkinter and a Major League Baseball API to give fans and fantasy baseball managers quick and easy team stats and standings, along with roster depth charts, game schedules, and transactions.