At Netflix, we reach out to our members about new recommendations in the most effective way, through emails and notifications. We deliver billions of messages per year, and we work on the algorithms that decide what to send, when and to whom. The personalized system employs algorithms at the intersection of Personalization, Reinforcement Learning and Causal Inference.

In this talk, we will take the audience through a tour of the continuous explore and exploit system we have iterated on, and showcase a few particularly complex and fascinating challenges with offline evaluation and experimentation.

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Grace Huang

Machine Learning Engineering Manager | Netflix

Grace Huang is a Machine Learning Manager at Netflix, where she leads a team that innovate on personalized messaging and growth algorithms. Prior to Netflix, Grace has led a variety of personalization and recommendation algorithm developments at Pinterest and PopSugar. She is passionate about applying pragmatic and scalable algorithmic solutions to real-world problems.

Grace Huang