AI Consultant · Dallas, Texas
PhD, Industrial Engineering · 12+ years building decision systems
I help companies put AI into the decisions that move their numbers, and prove that it did. Most of my career has been spent inside large operations: supply networks, store fleets and pricing desks, where a model only counts once people trust it enough to act on it.
Optimization and experimentation built around a specific business decision: where to place inventory, how to set a price, which network design holds up when things go wrong. I scope it in revenue, margin or cost first, then pick the simplest method that gets there.
Many teams can't say what their AI spend returned. I set up A/B tests, bandits and causal methods where clean experiments aren't possible, so Finance gets numbers it can audit and product teams get a method they can reuse without me.
Architecture, monitoring, versioning and ownership, so a model survives its first quarter in production. I work alongside your engineers and leave behind templates and documentation the team owns.
Built a causal measurement practice from a five-person seed team to 13 people. Its templates and method guide are used by 130+ product managers.
Stochastic network optimization across 3,200+ demand sites to unify two supply chains. INFORMS Franz Edelman semi-finalist, run by 160+ strategy users.
Led a team that grew from 2 to 10 and took cloud inbound scheduling from prototype to 600+ clubs in six months, at 99.9% uptime.
Routing and yield optimization on 2 PB of trucking data. Annual supply planning for a consumer electronics line, with planning cycles cut by about 40%.
Python, SQL, Java · Pyomo, Gurobi, HiGHS · AWS, Databricks, Azure, GCP · MLflow, Streamlit · Claude, Gemini, Google ADK
Have a decision you'd like to put on firmer ground? Find me on GitHub.