Invited Talks

Search, Pricing and Marketplace Dynamics at Airbnb

Bar Ifrach

Director of Data Science at Airbnb

Happy for Two (or Three): Joint Revenue Optimization for 2-Sided Parties for Promoted Listings at Etsy

Liangjie Hong

Head of Data Science at Etsy

An Overview of Surge Pricing

Hamid Nazerzadeh

Research Scientist Uber

Data Science for Netflix's Original Content

Kelly Uphoff

VP Content and Marketing Science and Analytics at Netflix,

Ashish Rastogi

Senior Data Scientist at Netflix

Netflix was a trailblazing innovator in machine learning as applied to personalization and recommendation systems but there are many other applications of machine learning at Netflix, especially as we further evolve into a global entertainment company. This talk will give an overview of how machine learning is leveraged before content launches on Netflix and how machine learning can support the creative process and serve as a tool for decision makers in our content and marketing organization. The process of creating content is a high-touch, creative endeavor so we need to be similarly creative in the machine learning innovations we develop. From neural nets that predict audience size for content that doesn't exist yet, to NLP and deep learning techniques that mine scripts to highlight properties we need legal clearance for, we are building unprecedented innovations. The talk will also broadly cover the challenges we face in this space, including data scarcity and making ML interpretable for non-technical stakeholders.