Intern, Data Science-Remote

Overview

Since our founding in 1924, we've cut cardiovascular disease deaths in half, but there is still so much more to do. To overcome today's biggest health challenges and accelerate this progress, we need passionate individuals like you. Join our movement, be part of the progress, and help ensure a healthier future for all. You matter, and so does the impact you can make with us.

The American Heart Association's Internship Program provides college students with hands‑on experience in various facets for individuals interested in gaining work experience with a non‑profit, voluntary health organization. This internship supports the Data Science team and provides hands‑on experience in data science, data engineering, and statistical modeling within clinical and biomedical research settings. Interns will contribute to key initiatives, including the development of agentic workflows and the exploration of advanced analytical and engineering methods. The role offers opportunities to collaborate closely with cross‑functional teams and to contribute to impactful, real‑world projects that drive research innovation and data‑driven decision‑making.

The Association offers many resources to help you maintain work‑life harmonization through your changing needs and life situations. To help you be successful, you will have access to Heart U, our award‑winning corporate university, as well as training and support locally and through our National Center.

Internship Overview

• Time Commitment: 20-25 hours per week
• Internship Duration: 9/8/26-12/11/2626
• Location: Remote
• Salary: $23.00 per hour

Internship Outcomes

Individuals participating in the internship program are provided with an opportunity to:

• Gain important and practical job skills to be successful in a non‑profit environment.
• Opportunity to explore a career‑path with a reputable voluntary health/service organization.
• Complete an internship that enriches your academic and professional resume as well as enriching your personal life by making a difference in the lives of others.
• Collaborate with interdisciplinary teams including clinicians, data scientists, statisticians, and engineers.
• Develop technical, analytical, and scientific communication skills applicable to both academic and industry careers.

Responsibilities

• Retrieve, integrate, and analyze large‑scale healthcare datasets, including electronic health records (EHRs) and clinical registries, to support clinical and population health research.
• Develop and maintain data processing, governance, and quality assurance pipelines to ensure reliable and compliant data workflows.
• Design and evaluate AI/ML solutions, including agentic workflows and foundation models, using cloud platforms such as Snowflake and AWS.
• Collaborate with cross‑functional teams to translate analytical findings into actionable insights and support data‑driven decision‑making.
• Contribute to code reviews, technical documentation, and the development of abstracts, manuscripts, and other scientific communications.

Qualifications

• Currently pursuing an MS or PhD degree in Data Science, Computer Science, Biomedical Informatics, Statistics, Engineering, Public Health, or a related quantitative field.
• Demonstrated ability to research health topics and translate findings into actionable guidance.
• Prior research or industry experience in biomedical informatics, clinical research, epidemiology, healthcare analytics, or related domains.
• Demonstrated proficiency in Python, R, and SQL, with experience developing reproducible data processing pipelines and analytical workflows for large‑scale datasets.
• Demonstrated experience developing, deploying, and evaluating ML and AI solutions, including large language models (LLMs), AI agents, and agentic workflows for data engineering, analytics, and scientific research applications.
• Proficiency with software engineering best practices, including Git‑based version control, code review, testing, documentation, and Agile project management tools.
• Experience working with cloud computing and/or high‑performance computing environments (e.g., AWS, Snowflake, Azure, GCP).
• Excellent communication, scientific reasoning, and critical‑thinking…