A classifier tells you what will happen. My work targets the harder question underneath it — whose decision can I actually change, and how few observations before I know for sure.
Prediction is table stakes. The projects I'm proudest of reframe the problem so the answer is something a business can act on — and stay honest about what the data can and can't prove.
A churn classifier flags who will leave. A fraud model flags what looks anomalous. Useful — but it spends budget on people who'd stay anyway, and treats "flagged" as if it were "provably true."
I estimate the causal effect of an intervention per person, route budget only to the persuadable, and quantify detection latency under an opponent who's actively hiding. Then I report the honest number, not the flattering one.
Three end-to-end builds on real, messy data — a spatial model whose residuals recover a finding it was never told about, an operations system that goes from forecast to optimization to simulation, and the production monitoring that catches what drift detectors miss.
A run of explainable, decision-support ML — each one deployed as an interactive Streamlit tool, each pairing predictions with the reasoning behind them.
The stack behind the work — weighted toward Python ML, causal inference, explainability, and getting models out of the notebook and onto a URL.
Experience
Analyzed Trackman pitch and batted-ball data for 30+ players to support evaluation; assessed team and opponent tendencies through Synergy and scouting workflows.
Ran film analysis in HD Intelligence to identify high-efficiency shot zones.
Generated box scores and shot charts for 40+ players; produced five solo film segments coding in SportsCode.
Tracked live gameplay with DakStats across 20+ games.
Education
Graduate coursework spans data mining, machine learning, deep learning, NLP, time-series modeling, and visualization of complex data.
Open to new-grad data science roles · May 2027
Looking for new-grad data science and ML roles — especially anything applied, causal, or decision-support. Happy to walk through any project in depth, code and all.