I came up in IT support. Now I analyze the tech and energy companies I used to troubleshoot.
My background is in enterprise IT: I ran the operations, systems, and vendor decisions a whole organization depended on, and trained its staff to actually use new tools. That operator's view is what I bring to the desk now. I cover TMT, AI infrastructure, and energy as an independent analyst, with an MBA from Maryland Smith and CFA Level 1 in progress.
The pivot is the edge.
Most analysts covering the AI buildout learned the technology from earnings calls. I learned it from inside the IT department. Before business school I spent years in enterprise IT at Truth Initiative, a national public-health nonprofit in Washington, D.C., directing IT operations and vendor decisions, keeping the organization's systems and networks running, and building an AI enablement program that trained more than 100 staff. When the market started pricing data centers, interconnects, and power as the scarce assets of the decade, that background stopped being a detour and became the thesis.
The finance discipline came deliberately. An MBA at the University of Maryland's Robert H. Smith School of Business, analyst work in Smith's student-managed Global Equity Fund, and CFA Level 1 in progress. The standard toolkit, learned the standard way, so the differentiated part of my work is the judgment, not the mechanics.
TLCapital.AI is where I prove it. Full theses with DCFs, comps, and sum-of-the- parts builds. Conviction ratings I have to live with. Post-mortems when a call goes against me, written in the open, because a track record you can't audit isn't a track record. The site also runs a clearly labeled AI briefing pipeline I built and run myself, which is its own kind of evidence: I don't just write about these tools, I put them to work.
I'm based in Washington, D.C., open to relocating, and looking for an equity research seat, sell-side or buy-side, where an analyst who can read both a 10-K and a network diagram is useful.
How I think about research
The short version. The full process lives on the methodology page.
Independent, with a view
Every note takes a position and carries a conviction rating. No coverage for coverage’s sake. If I publish it, I have a view worth defending.
First principles, shown work
Segment builds, DCFs, comps, and sum-of-the-parts builds, with the assumptions visible. The deck behind every note is downloadable, so the work can be checked.
Public post-mortems
When a call goes against me, I write about it in the open: what I got right, what I got wrong, and what it changes. Judgment is a paper trail, not a highlight reel.
Experience
Global Equity Fund Analyst
June 2025 – May 2026University of Maryland, Robert H. Smith School of Business · College Park, MD
- Screened the Consumer and TMT sectors in LSEG Workspace for asymmetric risk/reward setups, deep-diving 15+ companies and surfacing 3 undervalued names with at least 15% projected upside.
- Built 5+ valuation models (DCF, trading comps, precedent transactions) across Consumer and TMT names including Alibaba and Sony, integrating 3-statement models from 10-K and 10-Q filings to pressure-test each thesis.
- Authored and delivered 3 buy/sell pitches to the investment committee, earning a 66% adoption rate and directing roughly $30K of deployment within a $650K endowment.
- Ranked positions by risk-adjusted return using Sharpe ratio and drawdown analysis to inform portfolio allocation.
Founder & Independent Equity Research Analyst
May 2026 – PresentTLCapital.AI · Remote
- Engineered "Hermes," a multi-agent research assistant on DeepSeek V4 that orchestrates specialized agents to define research goals, gather and synthesize data, and accelerate idea generation.
- Built LLM-driven workflows that summarize SEC filings and earnings transcripts and surface research signal for investment-thesis development.
- Developed automated data pipelines that collect and refresh financial data from market and filing sources, creating a repeatable backbone for AI-assisted research.
Information Technology Specialist
August 2021 – May 2026Truth Initiative · Washington, D.C.
- Designed and delivered an AI workflow and automation training program to 100+ staff (about two-thirds of the organization), and consolidated the company onto two approved AI platforms (Microsoft Copilot and Claude).
- Wrote SQL queries against a 150-endpoint asset database to automate inventory audits and reconcile records, replacing manual tracking.
- Directed enterprise IT operations and vendor evaluation across a $15–20K monthly budget, an operator’s lens now applied to judging the execution and scaling risk of growth-stage technology companies.
Financial Analytics Tool
Self-Directed Project · Python · Yahoo Finance API
- Built a Python tool integrating the Yahoo Finance API to auto-update 5+ DCF models with live market data, eliminating manual entry and enabling continuous valuation tracking.
Education
- MBA, Finance
University of Maryland, Robert H. Smith School of Business · Expected August 2026 · GPA 3.69
- B.S., Business Administration
Towson University · June 2023
Credentials & Certifications
- CFA Program Level I Candidate (exam August 2026)
- CompTIA A+
- CompTIA Network+
- Bank of America & Citi Investment Banking Job Simulations (Forage)
Skills
Claude, ChatGPT, Microsoft Copilot, DeepSeek V4; multi-agent orchestration, LLM filing & transcript analysis, automated data pipelines, agentic workflow design, prompt engineering
Python (Pandas, NumPy, Yahoo Finance API, DCF automation), SQL
LSEG Workspace, Bloomberg Terminal (familiar); advanced Excel (DCF, trading & transaction comps, 3-statement models), PowerPoint