The analytics translator behind the work

I started at IBM in Research Triangle Park as a Consulting IT Specialist. The work was technical sales and proofs of concept, training partners and clients, and collaborating with the IBM Watson Research Center. I also wrote — two IBM Redbooks went out under my name. That stretch taught me how enterprise software actually gets sold, built, and adopted, and how to explain something technical to a room that needs to act on it. That last skill turned out to be the whole career.

Running alongside the enterprise work was teaching. I taught Java, object-oriented analysis and design, and databases at Wake Technical Community College. Teaching forces a particular discipline: if you can't make a hard idea land with someone who is hearing it for the first time, you don't understand it well enough yet. That thread never stopped — it continued through a graduate assistantship at Fayetteville State University, where I led analytics and supply-chain study sessions.

From there the work moved across sectors and stayed close to the hard problems: enterprise transformation experience across healthcare, technology, and nonprofit sectors. I built SOA web services at GlaxoSmithKline, delivered technology at Benefitfocus first as a senior engineer and then as a delivery manager, and configured PolicyCenter as a senior consultant at Guidewire, collaborating with their Toronto development center. Different industries, same job underneath: translate between what the technology can do and what the business needs it to prove.

Then I went independent. Under my own consulting practice, I served FUNCRISA, a nonprofit healthcare provider in Guayaquil, Ecuador. Working directly for a client with real constraints sharpens you. There's no abstraction layer between your analysis and whether the thing actually works for the people relying on it.

Now I've pointed all of it at analytics. I'm completing an MBA in Business Analytics (4.0 GPA) at Fayetteville State University. My capstone, EV Pulse NC, is a five-phase pipeline that prioritizes North Carolina's $109M in federal EV-charging funds across all 100 counties — built on 8,000+ vehicle-registration observations, weighing Justice40 equity alongside demand to produce a NEVI Priority Score. It took second place at the 2026 FSU MBA Showcase. My toolkit runs on Python, SQL, and SAS (Viya and Studio) for spatial and statistical analysis, and I build AI that actually works — Lodestar, an agentic assistant I rebuilt myself, decides when to retrieve and grounds its answers in a real knowledge base, with a hosted build live today. It grew out of IgniteAI, the career assistant my team built when I led it to first place at the 2024 HP Future of Work Accelerator.

Good analysis answers a question. Great analysis survives the room where someone tries to tear it apart. I build for that room. I want the methodology to hold up when a skeptic pushes on it, the data to trace back to its source, and the recommendation to be one a leader can actually defend in front of people spending real money. I'd rather hand you a conclusion you can stand behind than one that only looks good in a slide. Concrete over clever, every time.