Thanks to the rapid growth in data resources, business leaders now appreciate the importance (and the challenge) of mining information from data. Join in as a group of LinkedIn’s data scientists share their experiences successfully leveraging emerging techniques to assist in intelligent decision making. You’ll gain an overview of the challenges in leveraging data resources to drive business decisions, explore the lifecycle and closed-loop solutions to data-driven decisions, and discover cutting-edge techniques and solutions for the most critical business decisions.
Chi-Yi Kuan is director of data science at LinkedIn. He has over 15 years of extensive experience applying big data analytics, business intelligence, risk and fraud management, data science, and marketing mix modeling across various business domains (social network, ecommerce, SaaS, and consulting) at both Fortune 500 firms and startups. Chi-Yi is dedicated to helping organizations become more data driven and profitable. He combines deep expertise in analytics and data science with business acumen and dynamic technology leadership.
Yongzheng Zhang is a senior manager of data mining at LinkedIn and an active researcher and practitioner of text mining and machine learning. He’s developed many practical and scalable solutions for utilizing unstructured data for ecommerce and social networking applications, including search, merchandising, social commerce, and customer-service excellence. Yongzheng is a highly regarded expert in text mining and has published and presented many papers in top journals and at conferences. He also organizes tutorials and workshops on sentiment analysis at prestigious conferences. He holds a PhD in computer science from Dalhousie University in Canada.
Xiaojing Dong is head of marketing science and a staff data scientist on the data science team at LinkedIn. She’s also an associate professor of marketing and business analytics at Santa Clara University, where she led the effort in designing and starting a popular Master of Science program in business analytics and served as the founding director. She helps translate business and marketing problems into data questions and apply analytical techniques into solving such problems to assist business decisions.
Burcu Baran is a senior data scientist at LinkedIn. Burcu is passionate about bringing mathematical solutions to business problems using machine learning techniques. Previously, she worked on predicting modeling at a B2B business intelligence company and was a postdoc in the Mathematics Departments at both Stanford and the University of Michigan. Burcu holds a PhD in number theory.
Emily Huang is senior manager of the data science team at LinkedIn. Emily has more than 10 years of experience in security data science, customer operation analytics, and data product development across industries including finance, ecommerce, social networks, and SaaS. She’s passionate about translating business problems into qualitative questions, solving them by synthesizing and mining large-scale data, and driving business decisions. She’s also enthusiastic about developing the data science community via mentoring, volunteering, and being an evangelist of data-informed culture for all organizations.
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Is it possible to share the presentation slides? Thanks!
This a great session. Could the presentation be made available?