Where I've worked, newest first. My resume has the bullet points. This page is the plain-English version, plus what I took away from each job.
I start in October and will work alongside classes this fall. First Analysis is an investment bank and venture investor in Chicago that works with growth companies. I'm joining the banking side.
↳ Goal for the fall: get faster at the things I've only done once or twice.
I worked on the sale of a physician practice to a PE-backed healthcare platform. The deal team was small, so I got real pieces of the work. I recast the practice's QuickBooks financials into a clean P&L and balance sheet, then built the bridge from reported earnings to adjusted EBITDA, which the buyer's valuation was based on.
I also pulled EV/EBITDA multiples for PE-backed healthcare platforms in PitchBook to frame the valuation range before negotiations, and I ran the diligence request log in Excel, flagging open items every week so both sides stayed on schedule.
↳ Biggest takeaway: most of the negotiating happens over the adjustments to EBITDA.
I split my time between two deals. The first was a company in pharma serialization, which is the tracking of individual drug packages through the supply chain. I did a SWOT, benchmarked it against competitors, and reviewed its product lineup to help sharpen how it would be pitched to buyers. Then I mapped 30 to 40 strategic and financial buyers and made a page on each one: what they'd bought before, how the company would fit, and where the synergies were.
On a separate sell-side deal, I drafted 3 to 4 pages of the CIM, the document that goes out to potential buyers, covering historical financials, customer concentration, and competition.
↳ Biggest takeaway: a company can be really good and still be hard to sell.
I tracked KPIs for six B2B software companies in the portfolio, all in AI/ML or RegTech and based in the US or India. I did financial diligence on new SaaS investments, which meant going through cap tables, deal terms, and founder projections, and I co-wrote two investment committee memos on market size, competition, projections, and exit options.
The monthly KPI update was all manual, so I automated it in Python and made the portfolio review decks consistent. After that, nobody on the team had to pull that data by hand.
↳ Biggest takeaway: at the early stage, a lot of the decision comes down to the founder.
A search fund is when someone raises money to find, buy, and run one small company. My job was helping find it. I screened 200+ lower-middle-market businesses on how steady their revenue was, how clean their EBITDA was, and how much they had to keep spending on equipment. Each week I turned 50+ data points into screening memos on the ones worth a closer look.
I also built three AI workflows for reading filings, scanning news, and writing one-page target summaries. The whole fund started using them, and they saved the team about 15 hours a week.
↳ Biggest takeaway: most small business owners aren't thinking about selling.
The clothing brand I co-founded at 17. I handled pricing, vendors, and planning our drops, built a campus creator program across 10+ schools, and built software to keep track of it all.
A fellowship, a pitch competition, and some volunteering.
An 18-month-plus fellowship with coaching, mentors, case studies, and time with Fortune 500 partner companies.
I was picked for the first one. Our team pitched selling a 51% stake in Athleta and keeping 49%. We built a DCF, sum-of-the-parts, and buyer returns model ($561M enterprise value, 19–20% IRR) and wrote a four-page memo.
With Dr. DeWone Bennett, I put 150+ scholarships and college resources into one database for Dallas-area teens, and talked with 15 students about how I got to college.
I was peer-nominated to our school's suicide prevention and mental health group. I led 8 student workshops and helped run Hope Week and the district's Hope Walk.
Minors in Business and Generative AI
Class of 2029 · Nashville, TN
Classes so far: financial accounting, micro, macro, statistics, calculus
Wall Street Prep, Financial & Valuation Modeling: DCF, LBO, M&A, and comps.
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