In collaboration with Dr. Renyu Zhang, Professor of Operations Management at NYU Shanghai, and Arthur Pentecoste and Paul-Emile Gras, two graduates of the 黑料不打烊 Desautels Master of Management in Analytics (MMA), Prof. Maxime Cohen鈥檚 new book, is scheduled to hit shelves on January 3, 2022.
鈥�We wanted to build a case study based on real-world experience for a lecture, to teach students how to predict demand,鈥� Cohen explained. 鈥淭here was so much material, the case study was going very well and was 60, 70, 80 pages long. I told [Arthur and Paul-Emile] 鈥楲ook, unfortunately, this is not a case study anymore. I think that this is becoming a book.鈥�
Working with Prof. Cohen as research assistants when the project began, Pentecoste and Gras were able to work closely with the professor till to the end, even once they had graduated and left their roles as research assistants, moving onto careers as data scientists.
鈥淭he way it would work typically is we would collaborate with [Prof. Cohen] on how we were going to approach a problem, and the different steps, and we would just receive guidance and help troubleshoot,鈥� said Pentecoste. 鈥淎nd in the meantime, there would be some heads down work on our end where we were just implementing several algorithms and working on the pure coding.鈥�
While there was one target for the teaching case study that was originally planned, the new book format meant that the target audience could be expanded upon. Cohen explained that the book is not only aimed at students in programs like 黑料不打烊鈥檚 MMA, but also at data scientists and retailers who might hire scientists to implement the tools and processes outlined in the book.
The goal of the book is ultimately to demystify how predictive analytics can be used in a retail context and how retailers can monetize historical data, to do better in the future.
鈥淭he book includes detailed implementations, along with comprehensive Jupyter notebooks. [There is also] a data set available for download with the book. In fact, the book is accompanied by the website DemandPredictionBook.com鈥� Cohen said.
What was perhaps most helpful for Cohen was the fact that Pentecoste and Gras fell right into that target demographic, allowing them to provide valuable insight on the digestibility of the methods outlined in the book.
鈥淸We were able to] explain some algorithms with words that were simple and more accessible,鈥� Gras said. 鈥淚 mean, we both have engineering and math backgrounds in our undergrad, but most of the models covered in the book, two years ago, we did not know. It was [fresh] in our heads, what would have helped us better understand all the topics.鈥�
Both former students appreciated the opportunity to work with Cohen and their other co-author on this project, citing it as a very important source of hands-on experience headed into the workforce.
鈥淚 think the fact that it's a professor that has done a good amount of publishing papers and that has been recognized, he has credibility, it helped with my resume and with screening processes,鈥� said Pentecoste. 鈥淎s a research assistant, because we鈥檝e done some consulting with some companies, we鈥檝e done some research, it was a way to show proficiency in analytics and using those tools.鈥�
It seems the feeling was mutual, as Cohen expressed how much he enjoyed working with Pentecoste and Gras.
My experience working with Arthur and Paul-Emile was great. I鈥檓 very happy with my collaboration with them,鈥� Cohen said. 鈥淭hey were very responsible and eager to contribute to the book. They were the right judges to confirm the best way to tailor the content of the book for the target audience. They also had quite a big role in terms of making the code top notch. They took a lot of time to make sure that all the codes and notebooks are well written and easy to follow.鈥�
With the publishing of this new book and his recent nomination as the Scale AI Research Chair in Data Science for Retail, it鈥檚 been an exciting time for Cohen, who plans to continue his work on demand prediction and retail analytics, while examining the challenges presented by COVID-19.
鈥淚'm also hoping to branch out and work on several other topics,鈥� Cohen explained. 鈥�The Chair will allow me to work on developing data science techniques for retail applications. We also want to make sure that all the methods have social impact鈥攕ustainability considerations will be at the core of the Chair. Another focus would be potentially emerging markets [and the] circular economy.鈥�
听
