The ideal candidate must be a PhD student in their 4th year or later, with research experience in online experimentation or causal inference. They should be proficient in R and/or Python, have excellent communication skills, and be self-motivated. Past publications and familiarity with SQL and git are preferred.

The Experimentation & Causal Inference Intern at Netflix will work on real-life decision-making challenges, collaborate with colleagues, analyze massive data sets, and present their work at internal forums.

Data

United States

San Francisco

Los Angeles

Large

Netflix is a leading global streaming service that offers a vast library of movies, TV shows, and original content to subscribers. Their primary goal is to provide entertainment and storytelling that captivates and resonates with audiences worldwide, transcending borders and demographics. Netflix's fundamental objective is to be the premier destination for viewers seeking diverse and high-quality content, fostering a culture of binge-worthy narratives and pushing the boundaries of digital entertainment.

Entertainment & Media

Netflix

Where you come to do the best work of your life. Follow @WeAreNetflix on Twitter, IG, Facebook, & Youtube for more

<ul><li>Netflix is the world's leading streaming entertainment service with 240+ million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Netflix is reinventing entertainment from end to end. We are revolutionizing how shows and movies are produced, pushing technological boundaries to efficiently deliver streaming video at massive scale over the internet, and continuously improving and personalizing how content is presented around the globe.&nbsp;</li><li>Throughout our business, Netflix employs a simple but powerful approach to product innovation and decision making: we ask our members, through experiments (online or quasi), which of several possible experiences resonate with them. To support experimentation at scale, we continuously invest in our&nbsp;democratized experimentation platform&nbsp;that supports contributions of metrics and inference methods from users of all backgrounds, and permits experimenters to use these building blocks to develop flexible and powerful workflows. We are always looking to improve our decision making capabilities by exploring, developing, and implementing new approaches to the design and analysis of randomized experiments, and by leveraging approaches from observational causal inference.&nbsp;&nbsp;</li></ul>

Currently Studying

Netflix is the world's leading streaming entertainment service with 240+ million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Netflix is reinventing entertainment from end to end. We are revolutionizing how shows and movies are produced, pushing technological boundaries to efficiently deliver streaming video at massive scale over the internet, and continuously improving and personalizing how content is presented around the globe. Throughout our business, Netflix employs a simple but powerful approach to product innovation and decision making: we ask our members, through experiments (online or quasi), which of several possible experiences resonate with them. To support experimentation at scale, we continuously invest in our democratized experimentation platform that supports contributions of metrics and inference methods from users of all backgrounds, and permits experimenters to use these building blocks to develop flexible and powerful workflows. We are always looking to improve our decision making capabilities by exploring, developing, and implementing new approaches to the design and analysis of randomized experiments, and by leveraging approaches from observational causal inference.  

Experimentation & Causal Inference Intern, Data Science & Engineering (Summer 2024)

Requirements

Responsibilities

Netflix

Mission & Purpose