I build pipelines, models, and dashboards that turn messy real-world data into decisions that actually matter. MS Data Science & Analytics at GVSU graduating Dec 2026. Worked across education, curriculum policy, and public health research. Ready to bring the same rigor to any industry where data drives outcomes.
I came to data science from mathematics, which means I actually like the hard parts. I've analyzed national curriculum data in Kenya, built ETL pipelines for thousands of students, run latent profile analyses on teacher burnout, and written enough DAX measures that they appear in my dreams.
What drives me isn't the field, it's the problem. Give me a messy dataset, a real question, and enough coffee, and I will figure it out. That's true whether the dataset is about schools, patients, weather, consumers, athletes, or anything else.
Outside of work: yoga keeps me sane, anime keeps me inspired, and adrenaline activities keep me honest about what I'm actually capable of. I'm also slowly working through a bucket list that includes competing on The Amazing Race and visiting all 7 continents, currently 2 down.
✦ dbt Fundamentals — in progress
Production-pattern pipeline: 5 modular phases, dual-target loading (SQLite + BigQuery), regex schema sanitization, structured logging, row-count validation. The kind of engineering that holds up under scrutiny.
Full KDD pipeline on 2,149 patients. 93.8% accuracy with a fully interpretable decision tree. Reframed clustering failure as a scientific finding about disease continuity, the kind of insight that only comes from rigorous analysis.
Rigorous statistical investigation; permutation tests, 10K bootstrap samples, Welch's t-test, proving poverty drives gun violence rates while population does not. Not a hot take. A finding.
Does family engagement close socioeconomic achievement gaps? Tested across 25K students, four statistical models, convergent findings. 18% stronger protective effect for low-income students. Answer: yes, and here's exactly why.
I'm not looking for a job in a specific industry; I'm looking for a role where the data is hard, the impact is real, and the team is serious. I've worked in education, public health, and curriculum policy. I'm equally curious about tech, sports analytics, fintech, consumer products, AI, and wherever else good data problems live.
Open to relocation — Florida, Atlanta, Austin, Dallas, D.C., North Carolina, California, and beyond.
Whether you're hiring, collaborating, or just want to talk data, I'm always up for a good conversation.