Currently an Extern @PfizerThird-year Northeastern student learning to apply economic reasoning and data skills to real problems. Building a foundation for analytic and product work.
A small collection of class projects, data exercises, and prototypes that demonstrate my approach to economic questions, analysis, and product-minded solutions.
Built a full-stack risk analytics platform that computes portfolio risk metrics, stress scenarios, and optimization weights for investment decision-making; Integrated real-time macro data from FRED and Polygon.io to generate portfolio sensitivity through changing interest rates, inflation, and market context; Developed a sleek dashboard using React.js and Node.js to make complex analytics more accessible for finance users
Analyzed competing companies’ financial statements to calculate liquidity, profitability, leverage, and credit risk; Co-authored a financial report for creditors to determine short-term loan risk and borrower repayment capacity; Leveraged AI to support corporate credit risk assessment and develop loan approval recommendations; Presented findings through a financial analysis report using accounting data, ratio analysis, and business evaluation
Third-year Northeastern student learning to apply economic reasoning and data skills to real problems. Building a foundation for analytic and product work.
I am Theo Brown, a third-year Economics student at Northeastern University working toward a bachelor’s degree. I have limited formal work experience and I am exploring how economic analysis, data, and product thinking fit together as I prepare to start my career.
Externships
Pfizer Advanced: AI-Powered Document Insights & Data Extraction Externship
In progress
Experience
Founder
J2J · May 2025-Aug 2025
Marketing Volunteer
Electrify Medford · Mar 2025-Apr 2025
Sales Representative
H&M · May 2024-Aug 2024
Education
Northeastern University, D'Amore-McKim School of Business
Candidate for BS in Economics/Business Administration
Skills
Built a full-stack risk analytics platform that computes portfolio risk metrics, stress scenarios, and optimization weights for investment decision-making; Integrated real-time macro data from FRED and Polygon.io to generate portfolio sensitivity through changing interest rates, inflation, and market context; Developed a sleek dashboard using React.js and Node.js to make complex analytics more accessible for finance users
Analyzed competing companies’ financial statements to calculate liquidity, profitability, leverage, and credit risk; Co-authored a financial report for creditors to determine short-term loan risk and borrower repayment capacity; Leveraged AI to support corporate credit risk assessment and develop loan approval recommendations; Presented findings through a financial analysis report using accounting data, ratio analysis, and business evaluation
✅ Verified by Extern · ⏱️ In progress
Prototype AI-powered document intelligence with Pfizer—using OCR, LLMs, and RAG to automate real enterprise PDF workflows and build a standout portfolio project.
The project prototyped AI-powered document intelligence for enterprise PDFs, combining OCR, large language models, and retrieval-augmented generation. Work included researching model architectures, mapping data extraction pipelines, and assembling a proof-of-concept pipeline that processed and indexed document content.
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I researched core LLM concepts and their application to document pipelines, then translated those concepts into a technical outline that fed the prototyped extraction and retrieval workflow.
