Michael P. Stolz, P.E.
About Michael P. Stolz, P.E.
Michael P. Stolz, P.E., is the Director of Manufacturing Technology and Data Analytics at Bristol Myers Squibb, with 35 years of experience in engineering, technology, and manufacturing across the pharmaceutical, chemical, and agricultural chemical industries.
Title
Michael P. Stolz, P.E. is currently the Director of Manufacturing Technology and Data Analytics at Bristol Myers Squibb in Princeton, New Jersey.
Current Role at Bristol Myers Squibb
As the Director of Manufacturing Technology and Data Analytics at Bristol Myers Squibb, Michael Stolz leads an engineering group with an annual capital budget averaging $120 million. His responsibilities include process design, product tech transfer, equipment life cycle management, supply chain, qualification, and validation. He also spearheaded the implementation of continuous manufacturing within the network and developed a cloud-based platform for advanced multivariate process control using AI and machine learning.
Previous Industry Experience
Michael Stolz has accumulated 35 years of experience across Engineering, Technology, Manufacturing, R&D, Supply Chain, and Quality in the Pharmaceutical, Chemical, and Agricultural Chemical industries. His previous roles include Associate Director at Merck, Senior Process Engineer at FMC Corporation, and Research Engineer at Pfizer. He has been involved in the design, construction, and startup of 20 manufacturing plants globally, generating combined revenues of $500 billion.
Education and Certifications
Michael Stolz holds Bachelor’s and Master’s Degrees in Chemical Engineering from Manhattan College and an Executive Graduate Level Degree in Business Data Analytics from Harvard University. He is a certified Lean Six Sigma Black Belt and is licensed as a Professional Engineer in Pennsylvania and New York.
Achievements in Manufacturing and Technology
Throughout his career, Michael Stolz has been instrumental in producing a trillion doses of life-saving medicines. He played a key role in developing smartphone-based process data analytics to monitor performance and quality in real-time. His skills in Monte Carlo Probability Analysis, R-Studio Statistics Programming, Python Programming, and AI/Machine Learning have positioned him as a leader in manufacturing technology and data analytics.