Sylvester Juwe
British Gas, UK
Keynote: J Comput Sci Syst Biol
Listening to the voice of customers plays a prominent role in a customer-centric business strategy. But with the business environmentâ??s increased complexity and dynamism for a customer-centric business to thrive in its value delivery, there is a growing need for personalization of business offering and continuous evolution of business decisions in such a way that they align with changes in customer needs. These requirements could be challenging, particularly in organizations with a large customer base. In response, this talk presents how advanced analytics and machine learning techniques have enabled operational efficiency and business effectiveness in large organizations. Specifically, this address highlights how tree-based machine learning methods have been employed in understanding and prescribing solutions to complex and evolving operational business problems. Furthermore, it presents insights into, how uplift modeling has improved response rates and returns on marketing spends in large-scale targeted campaigns. Underpinning this talk is a discussion of the leadership approach that informed these innovations.
Sylvester Juwe is a highly experienced and qualified Artificial Intelligence Lead, currently a Senior Data Science Manager at British Gas, United Kingdom. Operating at strategic levels, he leads on the leveraging sophisticated machine learning and big data analytics and capabilities in enabling and driving business strategy thereby creating business value. He has experience in the exploitation of a range of data mining, advanced analytical and artificial intelligence techniques to understand customer behavior, derive critical insights, optimize operations and solve complex business problems. s.juwe@cantab.net
Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report
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