Summary
Dan Morris is a Staff Data Scientist with 12 years of experience building and leading full-stack data science and engineering teams to deliver production-grade analytics and forecasting pipelines. He specializes in modeling the electric grid—demand and generation forecasting, AMI/SCADA data management, DER adoption/sizing, and graph-based network modeling—and has led large, bottom-up forecasting efforts used to inform decarbonization policy and planning. A pragmatic practitioner, he prioritizes solving real-world problems over chasing the latest algorithms and excels at integrating data science work into agile software development. Technically, he’s strong in scalable distributed data pipelines, entity resolution, graph modeling, and taking ML from prototype to production while coaching teams to write production-quality code. He’s led teams at Kevala (including the CPUC High DER study), run engineering for EV charging intelligence, and now contributes at SPAN, bringing both managerial scale and hands-on delivery. Before data science he honed probabilistic thinking as a professional poker player and coach—an unconventional background that sharpened his rapid decision-making and risk modeling skills.
12 years of coding experience
11 years of employment as a software developer
BSE BA Mechanical Engineering Mathematics, BSE BA Mechanical Engineering Mathematics at Duke University
Data Wizard Data Science, Data Wizard Data Science at Zipfian Academy