David Stuebe

About David Stuebe

David Stuebe is a staff machine learning engineer at Think Labs AI with two decades of experience in machine learning, near real time data analytics and forecasting. Starting his career in Ocean Science, David worked in numerical ocean & weather prediction, creating a forecasting system used by the US Coast Guard and the National Weather Service in the Gulf of Maine. After three years as lead developer for Data Management on the NSF Ocean Observatories Initiative Cyberinfrastructure program he transitioned to a Data Engineering position with Upserve, a B2B SaaS startup in the hospitality industry. Upserve was acquired by Lightspeed, an omni channel sales company, to bring the descriptive, prognostic and proscriptive insights David helped build to their global platform. Since transitioning to the electric utility industry with Camus Energy in 2021, David has brought his experience with machine learning, numerical weather prediction data and scalable platform engineering to bear on the challenges of the renewable energy transition in the utility industry. Starting at Think Labs in 2025 David will be deploying physics informed deep learning to power flow modeling. David has a BS in Earth & Ocean Science from Duke University and MS in Ocean Physics from the Massachusetts Institute of Technology and Woods Hole Oceanographic Institute.

Experience

1. Staff Machine Learning Engineer

   Thinklabs Ai

   Jan 2025 — Present · Providence, RI, US

   At Think Labs I develop machine learning solutions for the utility industry and deploy them at scale. We are accelerating the pace of change towards decarbonization and electrification. That means improving grid safety, grid reliability and grid resiliency in the face of growing stress while reducing the cost of service using data driven machine learning solutions.

Education

• Duke University

  Bachelor of Science - BS, Geological and Earth Sciences/Geosciences

• Duke University

  BS, Earth Ocean Science

  1998 — 2002

• Massachusetts Institute of Technology

  MS, Physical Oceanography

  2002 — 2005

Skills

• Oceanography
• Scientific Computing
• Grid Computing
• High Performance Computing
• Linux
• Data Management
• System Architecture
• Analysis
• Physics
• Parallel Programming
• Software Engineering
• Science
• Gis
• Fortran
• C#
• Distributed Systems
• Matlab
• Coastal
• Remote Sensing
• Git
• Environmental Science
• Java
• Software Development
• Python
• Modeling
• Latex
• Data Analysis