Tristan Arbus is an independent AI and data science leader with more than a decade of experience building production analytics, machine learning, and AI capabilities in complex operational environments. Most recently, he led enterprise data science capability-building in the energy sector, spanning technical strategy, platform and architecture decisions, cross-functional delivery, and the standards and workflows needed to move models from experimentation into reliable use. His work focuses on the systems around the model: evaluation, observability, feedback loops, governance, and human-in-the-loop processes that help teams detect failures, earn user trust, and connect technical performance to business outcomes. A patent holder with an earlier background in engineering and field operations, Tristan brings a pragmatic perspective to scaling AI—favoring measurable impact, operational reliability, and thoughtful execution over hype.