Tentative Schedule: (EST)
2:05pm: Optimizing Personalization Using Machine Learning & AI w/ Accenture
Retail has long pursued the “holy grail” of product offers and deals which result in both happier customers, and net sales or margin lift. For customers, this equates to Personalization – getting the products they want, for a better price, easier and faster. For the Retailer, this equates to an optimization problem. The Accenture team will talk about how we recently solved this challenge in production for a major US Pharmacy, using Machine Learning and AI.
Charlie is Accenture’s Capability Lead for Data Science in the Northeast Region, driving data science innovation at the intersection of data science, engineering, industry, and government. He works with clients across Health, the Public Sector, Communications, Media and Technology, Products, and Resources on data science and machine learning projects, with 6 years of experience in the firm. He is based out of NYC, where he also studied Mathematics at Columbia University. In coding, Charlie is strongest in Python, pandas, and numpy.
Hector is a data science consultant at Accenture NE region. Throughout his consulting years between Europe and the US, he has built and led data-driven solutions using cutting-edge techniques in the fields of machine learning & big data in various industries such as Healthcare, Banking, & Retail.
Kate is an Accenture Data Science Senior Analyst in the Northeast Region. She is motivated by developing rigorous answers to complex quantitative questions and excels in tackling problems from a multi-faceted understanding. Kate holds an undergraduate degree in Mathematics and an M.S. in Analytics.
Disclaimer: All views, thoughts, & opinions expressed in the webinar belong solely to the panelists, & not to the panelists’ employer, organization, committee, other group or individual.