With the exponential growth of data being collected from production, process, supply chain, IoT and business systems, modern manufacturers are sitting atop a wealth of untapped opportunity. Despite this, many are still grappling with how best to use their new data assets and what tools are at their disposal.
Artificial Intelligence provides a mechanism to leapfrog traditional heuristics and simple statistics by learning automatically from data and identifying hidden connections that were previously impossible to detect.
During this Tech Takeover, Soothsayer will share their approach to framing data science problems and insight from first-hand experience building solutions that improve processes, increase efficiency and reduce defects on the plant floor.
Craig Huffer, Lead Data Scientist, Soothsayer Analytics
Craig Huffer holds a PhD in Nuclear Physics from North Carolina State University. As part of his PhD work, he developed the analysis code for analyzing a state of the art neutron lifetime experiment and led efforts to calculate the systematic errors for that experiment. He has transitioned to data science, where he continues to leverage his experience in applying data analysis and visualization techniques to solve challenging problems using machine learning. He has implemented complex machine learning based solutions for various domains including multiple projects in manufacturing and is a Python enthusiast.