Skip to content
Moshe Rosenwein headshot

Moshe Rosenwein

Moshe Rosenwein

Director, Data Science and Analytics at Bayer Healthcare

Dr. Moshe Rosenwein is Director, Data Science and Analytics, at Bayer Healthcare. Prior to joining Bayer, he held similar positions at AT&T Bell Laboratories, Medco Health Solutions, Novartis, and Eisai. Moshe received his Ph.D. in decision sciences from the Wharton School, focusing on heuristic algorithms for solving discrete optimization models. He has published 20 peer-reviewed journal articles in management science professional journals and co-authored two textbooks on project management. He has presented talks and seminars at numerous professional conferences and universities. While at Medco, he led a cross-functional team in capturing a semi-finalist in the Edelman competition, recognizing excellence in the practice of management science. Moshe also serves as an adjunct professor at Columbia University, teaching a course in project management in Columbia’s School of Engineering.


Track: Machine Learning

Integration of Marketing Mix Modeling and Portfolio Optimization in Promotion Resource Allocation

Allocation of scarce promotion resources among competing brands in a portfolio is a key strategic planning decision in pharmaceutical marketing. Typical business questions include: (i) How effective were specific promotion tactics in the past as measured by return-on-investment (ROI)? (ii) Can the promotion budget for particular tactics for specific brands be modified going forward in order to efficiently increase revenue? Marketing mix (MMx) – a series of statistical, regression models – estimates the level of return associated with each level of promotion spend. The model generates response curves, for each tactic and brand across the portfolio. The response curves are the inputs into a non-linear programming (NLP) model that solves the portfolio optimization business problem. At Bayer Healthcare, we integrated MMx statistical models with an NLP optimization model. Our solution approach identified opportunities to both grow top-line revenue and profitability by optimally investing in various promotion tactics.