Undergraduate Summer Intern -UCLA Health Information Technology's Advanced Analytics (Data Science) Team

Details

Posted: 28-Apr-26

Location: Los Angeles, California

Categories

Operations

Internal Number: 151926635

Description

Summary Statement

This internship is embedded within UCLA Health Information Technology’s Office of Health Informatics and Analytics, supporting analytics and AI/ML use cases across clinical, operations, finance, quality, and research domains.

The Student Intern will gain hands-on experience across the end-to-end data and AI lifecycle, including data engineering pipelines, feature platforms, MLOps

practices, and high-performance computing (HPC) environments using cloud-based technologies such as Azure, AWS, and Databricks. Interns may also contribute to applied AI development and evaluation efforts, including generative AI experimentation, model validation, and responsible AI practices within healthcare analytics workflows.

Internship Objectives

By The End Of The Program, Interns Will

• Contribute production-ready code to data, ML, or infrastructure platforms
• Understand how enterprise AI/ML systems are designed, deployed, and governed in healthcare
• Collaborate with data engineers, ML engineers, architects, and researchers
• Deliver tangible artifacts aligned with UCLA Health analytics initiatives
• Gain exposure to applied data science workflows, including exploratory analysis, machine learning experimentation, and evaluation of AI model outputs
  
  

Key Focus Areas

Interns will work in one or more of the following areas, based on interest and team needs:

Data Analytics, Architecture & Engineering

• Building core data products and reusable data pipelines
• Developing data orchestration workflows and APIs
• Establishing data quality and observability foundations
  
  

ML Engineering & MLOps

• Feature engineering and feature store development
• CI/CD pipelines for machine learning workflows
• Monitoring, maintenance, and retraining of production ML models
• Collaborating with data scientists to operationalize models
  
  

AI Development & Data Science

• Exploring machine learning and generative AI approaches to healthcare analytics challenges
• Conducting exploratory data analysis and experimentation with AI/ML models
• Developing evaluation frameworks and metrics for AI model performance
• Contributing to responsible AI practices, including bias assessment, validation, and model evaluation
• Supporting prototyping and experimentation for emerging AI use cases across UCLA Health
  
  

Compute & Research Infrastructure

• Cloud platforms and HPC environments
• AI/ML workloads for clinical and research analytics
• Trusted research environments (e.g., ULEAD)
  
  

10-12 Week Deliverables

By the conclusion of the internship, each intern is expected to deliver:

Production-Grade Technical Artifact

Data pipeline, ML feature module, API, HPC configuration, or infrastructure component or AI/ML experimentation framework

Documentation & Knowledge Transfer

Technical documentation explaining design decisions, usage, and operational considerations

Quality & Reliability Contributions

Data quality checks, observability metrics, CI/CD integration, or validation scripts or AI model evaluation artifacts

Final Presentation or Demo

Walkthrough of project outcomes, lessons learned, and future improvement opportunities

Code Contribution to Team Repositories

Reviewed, tested, and version-controlled code aligned with team standards

Qualifications

Required:

• Currently pursuing a degree in Computer Science, Data Science, Engineering, or a related field
• Strong interest in data engineering, AI/ML, or compute infrastructure
• Comfortable working in collaborative, production‑oriented engineering teams
• Curious, detail‑oriented, and motivated to learn enterprise‑scale systems in healthcare
  
  

Desired Technical Skills

Programming Languages

• Python, SQL, and Java for data engineering and machine learning development
  
  

Cloud & Data Platforms

• Experience or interest in Azure and Databricks for analytics and ML workloads
  
  

Machine Learning & MLOps Concepts

• Feature engineering, feature stores, CI/CD pipelines, model deployment, and monitoring
  
  

Applied Data Science & AI

• Experience or interest in machine learning experimentation, natural language processing (NLP), or generative AI tools
• Familiarity with ML libraries such as scikit-learn, PyTorch, or similar frameworks is a plus
  
  

Data Engineering Foundations

• Building data pipelines, reusable workflows, APIs, and data quality mechanisms
  
  

High-Performance Computing & Infrastructure

• Exposure to HPC environments, AI/ML compute platforms, and research infrastructure
  
  

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About UCLA

At UCLA Health, you can help heal humankind, one patient at a time by improving health, alleviating suffering and delivering acts of kindness. As you do, you’ll achieve great things in your life and your career. We’re a world-class health organization with four hospitals consistently recognized among the nation’s very best as well as an internationally-renowned medical school, primary and specialty care clinics and much more. Within our dynamic, innovative and growing organization, you’ll find exceptional opportunities to make the most of your abilities in a supportive, empowering and inclusive environment. If you embrace our values of Integrity, Compassion, Respect, Teamwork, Excellence and Discovery we invite you to see all you can accomplish at UCLA Health.

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