About Me
Hi, I’m Milele Hallingquest
I’m an AI automation engineer and senior data analytics professional based in Atlanta, GA — and I’ve spent the last 15+ years doing one thing: turning messy, manual, data-heavy processes into systems that actually work.
I started my career as a logistics and business analyst, learning early on that the gap between what data could tell you and what most organizations actually knew was enormous. That gap became my focus. Over time I moved through roles in telecommunications, media, education, and banking — each one deepening my conviction that good data work, done well, changes outcomes for real people.
Why I Build What I Build
A few years ago I started asking a harder question: what if the organizations doing the most important work — in education, healthcare, public service — had access to the same intelligent automation that enterprise companies take for granted?
That question led me to found two businesses.
ScholarDollarz was built for students. The scholarship search process is broken — full of dead links, outdated data, and databases that don’t actually match students to opportunities they qualify for. ScholarDollarz uses AI verification, intelligent filtering, and 4,600+ researched scholarships to fix that.
Both businesses share the same core belief: that access to intelligent systems shouldn’t depend on the size of your budget or your organization.
What I Do Best
I’m most valuable at the intersection of data engineering, AI integration, and business context — the place where technical depth meets a clear understanding of what actually matters to the people using a system.
On the technical side, I work across the full stack: SQL and Python for data, FastAPI for APIs, MongoDB for persistence, NVIDIA NIM for LLM integration, and Docker + Railway + Render for deployment. I build Power BI and Tableau dashboards that executives actually use. I write pipelines that run reliably in production, not just in demos.
On the human side, I’ve spent 15 years translating between technical teams and business stakeholders — knowing which questions to ask, which metrics actually matter, and how to communicate findings in a way that leads to decisions rather than more meetings.
Outside of Work
When I’m not building, I’m studying markets — specifically options strategies on SPX and futures, with a focus on 0DTE approaches. It’s a domain that rewards the same discipline that makes good data science: rigorous thinking, pattern recognition, and knowing when the signal is real versus noise.
I also create content around scholarship opportunities, working to get information about ScholarDollarz into the hands of students who need it most.
Currently Open To
I’m actively exploring senior data analyst and data analytics engineer roles with organizations doing socially impactful work — education, healthcare, nonprofit, and public sector environments where better data decisions translate into better outcomes for people. My work increasingly bridges analytics and AI engineering, and I’m building toward a data science role as that trajectory continues.
If that’s you, I’d love to talk.