Grow your career at Cedars-Sinai!

The Enterprise Information Services (EIS) team at Cedars-Sinai understands that true clinical transformation and the optimization of a clinical information systems implementation is fueled through the alignment of the right people, processes, and technologies.

Why work here?

Cedars-Sinai Medical Center has been ranked the #1 hospital in California by U.S. News & World Report, 2023‑2024. When you join our team, you’ll gain access to our groundbreaking biomedical research facilities and advanced medical education programs. We offer learning programs, tuition reimbursement and performance-improvement projects so you can achieve certifications and degrees while gaining the knowledge and experience needed to advance your career.

We take pride in hiring the best, most hard-working employees. Our dedicated doctors, nurses and staff reflect the culturally and ethnically diverse community we serve. They are proof of our dedication to creating a dynamic, inclusive environment that fuels innovation and the gold standard of patient care we strive for.

What will you be doing in this role:

The Data Scientist Intern delivers analytical solutions using programming, data-mining, statistics, machine learning, and visualization techniques. Responsibilities include querying databases, data processing, supervised and unsupervised machine learning, deploying production models, and communicating findings. Writes clean, performant, reusable code to perform repeatable analyses and to train and deploy models to multiple environments.

• This internship is primarily focused on Generative AI and LLM's.
  
• Creates database-to-deployment pipelines for models using the necessary programming languages (primarily R, Python, SQL).
• Creates sustainable data science infrastructure and adheres to data analysis/machine learning best practices.
• Performs exploratory data analysis to gauge the need for or appropriateness of advanced analytical methods.
• Works with senior or lead data scientists’ business partners to identify areas where data science can best deliver value.
• Tests and validates code to ensure adaptability of data applications.