2026 Statistics Intern (PhD)

Company Description

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on X, Facebook, Instagram, YouTube, LinkedIn and Tik Tok.

Job Description

Envision spending your summer working with energetic colleagues and inspirational leaders, all while gaining world-class experience in one of the most dynamic organizations in the pharmaceutical industry. This is a reality for AbbVie Interns.  

The Statistical Sciences (Stats) organization is part of AbbVie’s Data & Statistical Sciences (DSS) organization and plays a vital role in supporting the company's strategic goals by providing data-driven insights and solutions. The department is responsible for conducting advanced statistical analyses, designing experiments, developing predictive models, and delivering data-driven insights to inform business decisions. The team works collaboratively with other departments across clinical development, regulatory affairs, and global medical affairs to provide statistical expertise and analytical support for various projects and initiatives across all phases of clinical development.  

The Stats organization is composed of highly skilled statisticians, data scientists, and analysts who are pioneers in generating and leveraging scientific evidence to provide new treatments that make remarkable impact for our patients. The team is committed to continuous learning and development, staying up to date with the latest statistical methods and tools. 

As a Stats intern, you will gain knowledge about the pharmaceutical industry, conduct research on one or more statistical topics, and support other projects as needed. Potential statistical topics include but are not limited to: 

• Deep learning 
• Historical data borrowing 
• Missing data imputation 
• Survival analysis 

At the conclusion of the internship assignment, interns will present proje