AI Data Engineering Intern (BS)

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

Organization Overview

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

Functional Overview

You will join the Clinical and Development area within Lilly’s Advanced Intelligence & Research organization, where we build and deliver advanced AI and data science solutions that accelerate clinical development and improve decision-making across the drug development lifecycle.

Data engineering is the foundation of that work. Our models and AI applications are only as good as the data beneath them, and the data that matters most in clinical development is genuinely hard: standardized clinical trial data, real-world and observational healthcare data, and large volumes of unstructured data, all of it governed and sensitive. Data engineers on our team build the pipelines, data models, and platform capabilities that make this data reliable, discoverable, and ready for analytics and AI at scale.

As an intern, you will be assigned a scoped project with real business impact and will work alongside experienced data and machine learning engineers. The work will draw on a common set of capabilities: designing and building pipelines that ingest, transform, and validate large and often messy datasets; modeling data so it can be used for analytics and machine learning; writing production-quality Python and SQL; applying engineering practices such as version control, testing, code review, and documentation; and partnering with data scientists, machine learning engineers, and clinical collaborators to understand what the data needs to support.

You might work with clinical trial data in industry-standard formats such as CDISC SDTM and ADaM, real-world and observational healthcare data, unstructured documents such as protocols and study reports, or the feature and serving layers that feed models and AI applications.