Data Scientist, Radiology and Imaging Sciences

Emory University

. Build and maintain large-scale multimodal breast imaging data pipelines .

Posted 11/2/2026full-timeAtlanta • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining large-scale multimodal breast imaging data pipelines, evaluating clinical AI screening models, and developing structured data extraction systems using LLMs. Proficient in statistical analysis, machine learning techniques, and querying relational databases to drive optimization in clinical outcomes and business strategies.

Highest-signal resume keywords

Expertise In R, SAS, Or PythonProficiency In SQLExperience With Machine Learning TechniquesExperience With Clinical And Medical Imaging DataExperience With Cloud Platforms

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical TheoryData Extraction SystemsPredictive AlgorithmsData MiningMachine Learning TechniquesRelational DatabasesLarge DatasetsClinical Analytics ResearchData-Gathering TechniquesData Science

Soft Skills

CollaborationCommunicationProblem-Solving

Tools & Technologies

GCPAzureDICOMEHRHL7/FHIR

Industry Keywords

Clinical AI Screening ModelsMultimodal ImagingNIH Research GrantsData ScienceBiomedical Informatics

Tech Stack

Tools & technologies

AzureCloudGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Build and maintain large-scale multimodal breast imaging data pipelines
Evaluate and validate clinical AI screening models
Develop structured data extraction systems using LLMs
Conduct clinical analytics research for internal and external stakeholders
Mine and analyze data from internal and external data sources
Drive optimization and improvement of operations, clinical outcomes, and business strategies
Work with organizational stakeholders to develop business solutions
Use large datasets and models with predictive algorithms to test the effectiveness of different courses of action
Assess the effectiveness and accuracy of new data sources and data-gathering techniques
Support externally funded NIH research grants

Requirements

What you’ll need

Master's or PhD in Statistics, Mathematics, Computer Science or another quantitative field
3 years of relevant experience
Expertise in at least 1 programming language, such as R, SAS, or Python
Proficiency in statistical theory and underlying mathematical distributions
Expertise in querying relational databases with SQL
Experience with machine learning techniques, including clustering, decision tree learning, and artificial neural networks
Ability to demonstrate real-world application of machine learning techniques
Preferred: Master's degree in Data Science, Applied Statistics, Biomedical Informatics, or related field
Preferred: 2+ years of data science experience
Preferred: Experience with clinical and medical imaging data, including DICOM, EHR, and HL7/FHIR
Preferred: Proficiency in Python, R, and SQL
Preferred: Experience with cloud platforms, including GCP and Azure
Preferred: Experience with ML pipelines

Benefits

Comp & perks

Equal opportunity employment
Reasonable accommodations for qualified individuals with disabilities
Participation in university programs and use of facilities without discrimination