Blog posts about Experimentation

We are constantly striving to improve the experience on LinkedIn for our members and customers, with research and exp...

Architecture and tooling behind machine learning at Zalando ...

Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, Colin McFarland, Mihir Tendulkar, and Travis Brooks

Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, Colin McFarland, Andy Rhines, Sophia Liu, Mihir Ten...

Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, Michael Lindon, and Colin McFarland

Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, and Colin McFarland

Quality of a client application is of paramount importance to global digital products, as it is the primary way custo...

Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, and Colin McFarland

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

Part 1 in a multipart series about decision making and experimentation at Netflix

The propensity score matching model powering how we optimize for long-term decision-making

Hear from some our data scientists working in Experimentation and Causal Inference

Co-authors: Min Liu, Vangelis Dimopoulos, Elise Georis, Jialiang Mao, Di Luo, and Kang Kang The LinkedIn ecosystem dr...

Challenges and solutions of our experimentation platform at Zalando ...

Netflix was a proud sponsor of the 2020 Conference on Digital Experimentation (CODE). Netflix data scientists were al...

Editor’s note: This blog post is the first in a series providing an overview and history of LinkedIn’s experimentatio...

We discuss key challenges and approaches we’ve been using to handle small sample size and limited pre-intervention da...

Computational causal inference brings a software implementation focus to causal inference