How Netflix Data Science Powers Global Entertainment

“Netflix is bringing engaging, culturally diverse stories to people all across the globe. With each original movie or TV show, we learn more about what our members want – and rest assured, they want an increasingly broad, deep, global, dynamic library!

Whether it’s planning how to satisfy these global tastes with the right content portfolio or personalizing recommendations to each member, Netflix relies heavily on data science techniques. This talk will highlight some of our core data science strategies and applications involving predictive models & algorithms, experimentation, and analytics.”


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About Caitlin Smallwood

Caitlin Smallwood is VP of Data Science and Analytics at Netflix, where she leads analytics, measurement and prediction, experimentation science, and algorithm research for all parts of the Netflix business.  She and her team enjoy tackling challenging initiatives such as: personalizing entertainment recommendations to each member; predicting the popularity of new Netflix movies and TV shows to inform content and marketing investments; optimizing studio production operations; researching new experimentation techniques; optimizing the delivery and quality of internet streaming; and driving key metrics and reporting.  Prior to joining Netflix in 2010, Caitlin worked at Intuit, Yahoo!, and several mathematical consulting firms (PwC, SRA).  Caitlin holds a M.S. in Operations Research from Stanford University and a B.S. in Mathematics from The College of William and Mary.