I am a graduate student at Arizona State University's W. P. Carey School of Business, pursuing a Master of Science in Business Analytics. My work is driven by a single belief: data only matters when it changes a decision.
With a technical foundation in Python, SQL, and Tableau, I specialize in translating raw operational signals into clear strategies, automated workflows, and deployed software that teams actually use day to day.
I am currently expanding my expertise through Lean Six Sigma Green Belt training, a commitment to the kind of continuous improvement and analytical rigor that separates noise from signal.
Every project I ship sits on the same triangle: rigorous analysis, transparent visualization, and a relentless process mindset borrowed from manufacturing.
Building reproducible pipelines and predictive models that ground decisions in evidence rather than instinct.
Designing dashboards and visual narratives that translate operational complexity into one clear chart.
Applying DMAIC, value-stream mapping, and statistical process control to eliminate waste at the root.
Two production tools and two operational research case studies. Every project tracks a measurable business outcome from first commit to last review.
A multi-user scheduling tool for W. P. Carey's Supply Chain department. Manages 58 faculty, 696 credit units and 185 sections per term with real-time conflict detection, instructor preference matching, and credit-load balancing.
A live ML platform that combines an XGBoost and LightGBM ensemble for appointment-duration forecasting with reinforcement-learning queue rebalancing. SHAP explanations keep every prediction auditable for clinical staff.
Analytical study modeling commercial route-level fuel consumption against payload, altitude profile, and weather. A gradient-boosted regressor identifies the top three controllable variables driving a projected 4.8% reduction in burn rate per block hour.
Statistical optimization of patient appointment slots using historical show-rate distributions. Power BI dashboards expose provider utilization, no-show risk by cohort, and the financial impact of dynamic overbooking thresholds.
Arizona State University · W. P. Carey School of Business
Graduate research and applied projects across operational analytics, optimization, and statistical modeling. Building production tools used by the SCM department.
Continuous Improvement Certification
Active training in DMAIC, statistical process control and value-stream mapping. Applied directly to scheduling and healthcare operations projects.
Independent project work
Shipped Python-based machine learning models behind public web deployments. Focus on explainability, lightweight infrastructure, and decision support for non-technical operators.
I am open to internships, full-time analyst roles and academic research collaborations starting Spring 2026.
The fastest way to reach me is direct email. For job opportunities, project collaborations or academic inquiries, please use the form so I can route your message correctly.
