Data Science R&D Graduate Intern

Highmark Health

. Apply advanced data science, machine learning, artificial intelligence, and software engineering techniques to complex clinical and healthcare challenges .

Posted 10/19/2026part-timeRemote • United StatesEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in advanced data science, machine learning, and artificial intelligence techniques applied to healthcare challenges, with a strong focus on predictive modeling, graph technologies, and medical image processing. Proficient in collaborating with multidisciplinary teams to develop innovative solutions using healthcare data.

Highest-signal resume keywords

Python ProgrammingMachine LearningGraph TechnologiesMedical Image ProcessingPredictive Modeling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceArtificial IntelligencePredictive ModelingGraphQLComputer VisionNLPSQLRelational Database ConceptsGraph Neural NetworksGenerative AI

Soft Skills

CollaborationCommunication

Tools & Technologies

NumPyPandasScikit-learnPyTorchTensorFlow

Industry Keywords

HealthcareClinical DataBiomedical InformaticsData ScienceElectrical Engineering

Tech Stack

Tools & technologies

GraphQLNumpyPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Apply advanced data science, machine learning, artificial intelligence, and software engineering techniques to complex clinical and healthcare challenges
Collaborate with researchers, data scientists, machine learning engineers, and software developers
Develop innovative solutions using clinical, medical, and healthcare insurance data
Contribute to research initiatives involving predictive modeling, artificial intelligence, graph technologies, computer vision, and generative AI
Design and optimize graph-based healthcare data models, GraphQL interfaces, GNNs, and GraphRAG architectures
Build medical image processing pipelines and computer vision models for clinical image analysis, anatomical segmentation, and pathology classification
Develop healthcare risk prediction, disease progression, and patient outcome forecasting models
Design and evaluate AI agent frameworks, NLP solutions, prompt engineering strategies, and clinical information extraction workflows
Assist with analytical solution design and development, model evaluation, and experimentation
Communicate findings to technical and business audiences
Participate in projects, initiatives, research, reporting, and related studies under supervision and mentorship

Requirements

What you’ll need

Applicants must be authorized to work in the U.S. independently; visa sponsorship is not offered
Bachelor’s degree
Pursuance of a graduate degree full or part-time in an accredited college or university
Currently pursuing a Master's or Ph.D. degree in Computer Science, Biomedical Informatics, Data Science, Electrical Engineering, Applied Mathematics, or a related quantitative discipline (preferred)
Strong programming experience in Python (preferred)
Experience utilizing NumPy, Pandas, Scikit-learn, PyTorch, and/or TensorFlow (preferred)
Proficiency in SQL and relational database concepts (preferred)