Nicole Radziwill

Nicole Radziwill, PhD, a seasoned professional with over 25 years of experience, excels in providing executive leadership in strategy and execution for industrial and high-tech organizations.

Specializing in Quality & Operational Excellence, Nicole bridges strategy, operations, and quality to drive performance improvement, leveraging AI, machine learning, and high-performance software teams.

She is a recognized author of 'Connected, Intelligent, Automated: The Definitive Guide to Digital Transformation & Quality 4.0' and 'Statistics (The Easier Way) With R, 3rd Ed', showcasing her expertise in quality management and data science.

With a diverse educational background spanning human factors engineering, operations management, atmospheric science, and technology management, Nicole brings a wealth of knowledge to her roles.

Having held key positions such as SVP Quality & Strategy at Ultranauts Inc, VP Global Quality & Supply Chain at Intelex Technologies Inc, and Editor-in-Chief at ASQ, Nicole has made significant contributions in quality management and data science domains.

Her extensive experience also includes roles as Associate Professor, Data Science & Production Systems at James Madison University, Executive Consultant at AUI, and National Examiner for the Malcolm Baldrige National Quality Award.

Nicole is a hands-on data scientist proficient in modeling with various programming languages and platforms, adapting from archaic to modern technologies.

A thought leader and innovator, Nicole has presented over 20 keynotes at professional and academic conferences, shaping the discourse on topics like Industry 4.0, Quality 4.0, and operational excellence.

Her skill set includes quality engineering, Lean, Six Sigma, agile methodologies, IoT, data management, and predictive analytics, making her a versatile expert in the industry.

Nicole Radziwill's comprehensive expertise, vast experience, and academic achievements solidify her position as a prominent figure in the fields of technology, quality management, and data science.