This is the fifth post in a multi-part series on how Netflix uses A/B tests to inform decisions and continuously...

Here we describe the role of Experimentation and A/B testing within the larger Data Science and Engineering...

Using experimentation as a mechanism to safely and quickly update Netflix client applications.

Sean shares his perspective on how nonlinear career trajectories make us better, and can bring unexpected benefits...

In the third installment of the Netflix analytics series, Alex helps mythbust some common misconceptions about...

Netflix was a proud sponsor of the 2020 Conference on Digital Experimentation (CODE), hosted by the MIT Initiative on...

We describe how to support content decision makers by leveraging machine learning and statistical modeling.

In the second in the analytics branding series, Rocio shares her perspective of the projects, technical skills, and...

This Q&A provides insights into the diverse set of skills, projects, and culture within Data Science and Engineering...

An Introduction to Analytics and Visualization Engineering at Netflix

We discuss some key challenges and approaches Netflix has been using to handle small sample size and limited...

Computational causal inference brings a software implementation focus to causal inference, especially in regards to...

In this tech blog, we report the current status of the SVT-AV1 project, as well as the characteristics and...

The paper gives a technical overview of AV1 - the first video codec standard from Aliance for Open Media (AOM).

We need an alternative to JPEG that a) is widely supported, b) has better compression efficiency and c) has a wider...

At Netflix, we regularly run experiments to improve the quality of our member’s streaming service. We rely on custom...

We are pleased to announce the open-source launch of Polynote: a new, polyglot notebook with first-class Scala...

A recap of the ML Platform meetup hosted at Netflix, Los Gatos on Sep 12, 2019 on the topic of Infrastructure for...