Applied scientist and machine-learning engineer with ten years of experience building
production forecasting, ranking, optimisation, and state-estimation systems. Owns the full
lifecycle from research design and point-in-time data pipelines through deployment,
calibration, monitoring, and retraining. Selected work includes a roughly 60% reduction in
live-event forecast WAPE against a prior-season-average baseline, real-time marketplace
allocation serving millions of users, space-surveillance filtering and sensor scheduling,
and a patented stochastic production-planning model. Currently building a full-stack
systematic-volatility research and execution platform; targeting quantitative research,
research-engineering, and quantitative developer roles in New York.
Own modelling and optimisation for a multi-brand auction and ranking system serving
millions of users per month.
Built end-to-end data pipelines and a feature store enabling real-time inference and
offline training from consistent feature definitions.
Established model-health and retraining frameworks covering calibration, drift, data
quality, and segment-level performance.
Partner directly with the CEO and CTO to convert ambiguous commercial goals into
experiments and evidence-based decisions.
Aug 2021 – Mar 2025
Lead Data Scientist
Ticketmaster
Cut live-event sales forecast WAPE by roughly 60% against a prior-season-average
baseline, using temporally dynamic gradient-boosted trees.
Translated business strategy into feasible technical roadmaps and led the team
delivering data-science products.
Developed feature-selection optimisation enabling faster deployment of new models
to production.
Oct 2018 – Aug 2021
Lead Space Algorithm Developer
Lockheed Martin · Special Programs
Developed a binary linear-programming solution for real-time sensor scheduling,
optimising space-surveillance operations under hard latency constraints.
Implemented particle filters producing actionable ephemeris for space surveillance,
and enhanced missile-interceptor performance through algorithm development.
Designed Kalman and Singer filter instantiation processes improving convergence on
late threat detections.
Feb 2016 – Oct 2018
Data Scientist, Defense Analytics
Boeing
Patented the F/A-18 Fleet Upgrade Model — a discrete-event simulation optimising
production under stochastic demand.
Developed genetic algorithms for multi-echelon inventory optimisation, resulting in
awarded production funding.
Led the data-science arm of the T-45 physiological events investigation, driving
root-cause identification.
2013 – 2016
Teacher & Football Coach
Teach for America
Classroom teacher and football coach through the Teach for America corps.
2006 – 2010
Sergeant & Instructor
United States Marine Corps
Non-commissioned officer and instructor.
Education
Degrees & study
M.Eng., Systems Engineering — Arizona State University
2015.
B.S., Applied Mathematics — University of Texas at Arlington
