I'm an Information Systems student at The University of Texas at Arlington, with a minor in Business Analytics. I started working on analytics projects because I wanted to understand what happens between receiving a raw dataset and presenting something a business team can actually use.
Most of the work here is built around practical questions: Which carrier is creating extra shipping costs? What causes flight delays? Which skills are showing up most often in analyst job postings? I use SQL, Python, Excel, Power BI, and Tableau to work through those questions.
I'm currently looking for data analyst, business analyst, and technology analyst internship and full-time opportunities.
This project uses U.S. Bureau of Transportation Statistics flight data to study airline, airport, route, and delay performance. I built a repeatable workflow for cleaning the flight records, checking data quality, creating a SQLite database, and answering operational questions with SQL.
What I worked on: operational KPIs, data validation, route analysis, delay causes, and SQL queries
Tools: Python, pandas, SQL, SQLite
I analyzed more than 24,000 analyst job postings to see which skills employers request, where analyst roles are concentrated, and how salaries differ across skills and locations. Python and pandas handle the data preparation, and the final results are presented in Tableau.
What I worked on: data cleaning, skill extraction, salary comparisons, location analysis, and dashboard design
Tools: Python, pandas, Tableau, Git
A smaller project focused on a common shipping problem: the amount quoted by a carrier does not always match the final invoice. The analysis compares UPS and FedEx shipments, calculates invoice variance, flags possible overcharges, and summarizes delivery performance by carrier.
What I worked on: invoice matching, variance calculations, exception flags, and carrier comparisons
Tools: Python, pandas, CSV
Analysis: Python, SQL, pandas, Excel
Visualization: Power BI, Tableau
Data and development: SQLite, Jupyter, Git, GitHub
My next project will move beyond a local CSV-to-dashboard workflow. I'm planning to use Azure for storage and orchestration, Snowflake for analytics, and an API as one of the data sources. The goal is to understand the full path from incoming data to a dashboard rather than adding cloud tools to a project just for the name.
I'm open to internship opportunities, project feedback, and conversations about analytics work.