Senior Data Scientist and IoT Practice Lead at Very
As a Senior Data Scientist and IoT Practice Lead at Very, Jeff McGehee works with clients to build powerful Internet-connected products. Jeff is naturally drawn to problems that most people consider “unsolvable,” and he enjoys solving those kinds of problems at Very.
In his role as Very’s IoT Practice Lead, Jeff is a regular contributor to the OTA (over the air) firmware update server NervesHub (currently in a pre-release stage), applying his learnings from our IoT projects. He also served as a machine learning and hardware solutions leader for Hop, a client we worked with to build the world’s first facial recognition-powered beer tap. During the project, Jeff leveraged his academic background in control systems and robotics to ensure a successful launch.
Before joining Very, Jeff was a research and design engineer at Variable, Inc., where he developed proprietary models for accurate color measurement; built custom Python packages for sensor calibration and data analysis; and built and deployed internal tools that allowed non-technical workers to apply machine learning models.
In addition to holding a patent for his work related to sensor calibration and color measurement, Jeff has published research on optimal control of hybrid powertrains for automobiles.
Jeff regularly speaks at national events about IoT development best practices and presented his academic research at the Society of Automotive Engineers World Congress. Jeff also founded Data Science Chattanooga, a meet-up for data science professionals in the Chattanooga area.
Jeff holds a BS in Mechanical Engineering from Tennessee Tech University, an MS in Mechanical Engineering from Tennessee Tech University, and an MS in Computer Science with a focus in Machine Learning from Georgia Institute of Technology.