Markuss.
Business Analytics at BYU-Idaho. Statistics and Data Science minors. 4.0 GPA. More interested in useful systems than impressive-looking dashboards.
I start with the system, not the chart.
I care about bottlenecks, thresholds, failure modes, and what happens after a decision is made.
I like work where the answer has to survive contact with real constraints.
Why healthcare keeps showing up.
Health challenges in my family changed how I think about useful work. They made healthcare feel less like an industry and more like a system where delays, capacity decisions, bad handoffs, and weak information can become personal very quickly.
That is why so much of my portfolio returns to patient access, radiology, readmissions, survival, pricing, and hospital operations. I want to build the platforms and decision systems that help complex organizations act earlier and operate better.
Manufacturing, logistics, markets, and digital products matter to me for the same reason: they are places where scale exposes weak assumptions and good systems thinking has visible consequences.
Enterprise scale, measured precisely.
The point is not to make more charts. It is to make a failure visible early enough that somebody can still act.
At Volvo Group, I am leading measurement work across Adobe Customer Journey Analytics, web funnels, vehicle configurators, forecasting, sentiment, and machine learning. The work spans migration and instrumentation, but it also reaches the commercial question underneath: where are high-intent users falling out, how quickly can we detect the change, and what should the business do next?
That same habit runs through the rest of my work. I build the evidence trail before the presentation layer, test the assumptions before selling the result, and leave the next person with something they can inspect and operate.
What I can build with.
Technical range matters most when it shortens the distance between a question and a working system.
Python & ML
pandas, NumPy, scikit-learn, XGBoost, SHAP, joblib, feature engineering, model comparison, and simulation.
SQL & Data Systems
Joins, CTEs, window functions, normalized schemas, analytics views, query design, ETL, and reproducible handoffs.
R & Statistics
Regression, hypothesis testing, interaction models, tidyverse workflows, package development, and Quarto publishing.
Simulation
Discrete-event systems, multi-agent markets, capacity constraints, stress propagation, parameter sweeps, and optimization.
Business Intelligence
Power BI, DAX, Power Query, executive KPI design, decomposition, forecasting, and Excel decision models.
Product Systems
Node.js, Electron, FastAPI, APIs, instrumentation, protected infrastructure, open-source delivery, and user-facing workflows.