Practice Director of Data Science & Applied AI

Zach leads the Data Science and AI practice at Neal.  In his role as director, Zach helps customers to develop strategies and models that weave data science and AI into core business practices.  Since joining Neal in 2014, Zach has worked extensively in the areas of predictive modeling (supervised and unsupervised learning), analytics, and deep learning.  Prior to joining Neal, Zach worked for eight years in the energy and high tech manufacturing space spanning roles in research and development, product development, and strategy.  Zach holds degrees in engineering and business from UC Berkeley and Georgia Tech.

  • B.S. Bioengineering – University of California Berkeley
  • M.B.A. – Georgia Institute of Technology
  • M.S. Mechanical Engineering – Georgia Institute of Technology