Summary
Natalie Low is an Associate Technical Consultant with over 11 years of experience delivering data-driven engineering solutions across energy, aerospace, and structural domains. She currently leads parametric, Monte Carlo–based cloud workflows to assess energy efficiency measures and code compliance for statewide studies, translating complex data into clear Python-based analyses and visuals. Her background spans machine learning, full-stack web development, and structural design—ranging from the movable trailing edge of the Boeing 787 to probabilistic seismic design tools—demonstrating a rare ability to apply quantitative methods across industries. A Master of Science in Civil Engineering (Structures) from the University of Washington, she combines rigorous technical training with a practical, results-oriented mindset. Based in San Francisco, she leverages cross-disciplinary skills to turn complex requirements into auditable, scalable solutions for energy policy and building performance. Her early roots in psychology with minors in math and chemistry hint at a broad analytical lens and a knack for communicating technical insights to diverse stakeholders.
11 years of coding experience