Hi, I’m
Product, data, and
practical problem-solving.
UNC-Chapel Hill, Class of 2027
Business Administration & Data Science
I’m a senior at UNC-Chapel Hill studying business administration and data science. I’m interested in the work that makes a product useful: understanding someone’s workflow, figuring out what needs to change, and working through the technical and business details.
At Fusia Health, I translated hospital feedback into requirements and a pilot plan for AI-assisted care transitions. At Cisco, I used Python and SQL to improve reporting and inform commerce decisions. Most recently, at Bank of America, I worked on the evidence and controls behind responsible AI use.
I’m exploring full-time opportunities starting in 2027. If my background could be useful to your team, I’d love to connect.
Say helloJUN–AUG 2026
AI Governance Intern
Built a SQL, Excel, and VBA workflow that populated 44 of 80 QA scorecard fields from a model ID. Validated it against manual scorecards, presented the methodology to AI governance, and handed it to the QA lead. Also optimized roughly eight reporting scripts and reviewed four AI/ML models, identifying gaps requiring model-owner follow-up.
SQL / Excel & VBA / AI governance
Read what I learned in AI governanceAUG 2025–
JUN 2026
Strategy & Operations Lead
Translated case-manager feedback from a 135-bed hospital into product requirements and a synthetic-data pilot plan for AI-assisted facility matching, referral packets, and communication. Segmented 300+ pharmacy prospects, generating eight qualified pilot opportunities. Built pricing and unit economics across three customer segments to assess the business case.
Product requirements / Pilot planning / Unit economics
Read what I learned at FusiaMAY–AUG 2025
Data Analyst Intern · Commerce Operations
Automated reporting across Jira, SharePoint, and Excel with Python, saving 40 hours of manual analysis each month. Used SQL and Tableau to evaluate 1,260+ commerce assets and recommend three content improvements adopted by leadership. Built an AI infrastructure ROI model across six partner teams to estimate potential time and labor savings.
Workflow automation / SQL & Python / ROI analysis
1st place · Milwaukee Bucks Data Analytics Hackathon
Our team analyzed where fans disengage using segmentation, Markov chains, and churn analysis. We turned the findings into a retention strategy, with recommendations designed to fit existing Bucks platforms, and presented it to Bucks and Modine executives.
Details on LinkedIn1st place · UNC & StatQuest R.E.E.L. competition
Yae Young Kim and I made a five-minute video explaining how bias influences machine learning models and real-world decisions. The challenge was to make a technical topic understandable without losing the substance. The competition was supported by Lightning AI, NVIDIA, and Posit.
About the videoFinalist · L.E.K. Consulting Case Competition
Evaluated adjacent growth opportunities for DiveCo and turned the analysis into a market entry recommendation for L.E.K. consultants. Our team placed among the top 15 of approximately 125 registered teams.
Semifinalist · P&G × UNC Marketing Club Case Competition
Analyzed consumers, competitors, and category trends to develop growth recommendations for Tide, Gain, and Downy. Presented the strategy to P&G representatives.