Online Causal Inference Seminar

Free and open to the public
All seminars are on Tuesdays at 8:30 am PT (11:30 am ET / 4:30 pm London / 5:30 pm Berlin).

Tuesday, February 9, 2021 [Link to join] (ID: 995 8569 5110, Password: 007080)

• Speakers: Martin Tingley and Jeffrey Wong (Netflix)
• Title: Supporting Innovation and Scale with a Democratized Experimentation Platform
• Discussant: Iavor Bojinov (Harvard)
• Abstract: The Netflix Experimentation Platform is democratized and modular: data scientists can contribute metrics, causal inference methods, and visualizations directly to the platform, and use these building blocks to compose flexible reports that flow through to our frontend UI. This contribution model supports rapid prototyping and innovation, as data scientists contribute directly to production systems. To ensure that the platform continues to support the required scale (number and size of tests), we've invested in Computational Causal Inference software that can analyze massive datasets with a variety of causal effects in a performant, general, and robust way.

This talk will focus on how our software systems improve research agility and enable causal inference to be easily integrated into large engineering systems. We'll talk through several ongoing lines of work to enable progressively more sophisticated causal inference models on our highly scaled platform, and what we’ve learned in the process.