About the role#
This internship focuses on experimentation and causal inference research to support Netflix's business strategy. You will work within the Data Science & Engineering organization to develop analytical products and innovative solutions for complex decision-making challenges across commerce, content, studio, and product development.
What you'll do#
- Develop innovative solutions to real-life decision-making challenges at Netflix.
- Collaborate with colleagues in the Data Science & Engineering organization and beyond.
- Manipulate and apply statistical methods to massive data sets.
- Present your work at key internal forums within Netflix.
What you'll need#
- Currently pursuing a PhD degree at an accredited university, with a graduation date of December 2026, Summer 2027, or later. You must be returning to school for at least one semester or quarter following the internship.
- Active research in online experimentation (such as sequential or adaptive methods), observational causal inference, or a related field.
- Proficiency in R and/or Python.
- Experience with SQL and version control systems like git.
- Strong oral and written communication skills.
- A record of past publications in relevant journals or conferences.
Location & details#
- Location: Los Gatos, California.
- Term: Summer 2026.
- Modality: On-site.
- Duration: Minimum of 12 weeks.
- Compensation: This is a paid, full-time internship.
How to get in at Netflix
Intern Insider's per-company playbook.
Securing an internship at Netflix requires speed because roles often receive high volumes of interest. Intern Insider sends an instant alert the moment a role matching your target is published anywhere, so you apply among the first. Early applicants get seen before the pile grows, which helps your profile stand out during the initial review. Beyond timing, networking plays a role in the hiring process. Intern Insider surfaces the recruiters behind the company's roles so you can reach out directly to ask about the role or a referral. Engaging with the right people materially improves response rates compared to submitting a cold application.
