The Eagle-Eye Suite and the Ophthalmic Engineering & Innovation Laboratory (OEIL) are seeking a highly motivated, technically skilled, and exceptionally organized Research Data & AI Systems Officer to oversee the management of large-scale ophthalmic imaging, clinical, and artificial intelligence datasets.
The Data Officer will ensure that data generated by all research imaging devices are securely transferred, organized, documented, and fully backed up on the laboratory’s network-attached storage servers. The individual will develop a centralized and searchable research database, maintain rigorous versioning and documentation of AI models, connect ophthalmic imaging devices to clinical systems, and support the deployment of AI algorithms within electronic medical record systems.
The position requires expertise in data management, databases, software systems, AI workflows, and technical problem-solving. It also requires excellent communication skills, as the Data Officer will work closely with clinicians, researchers, engineers, AI scientists, information technology teams, regulatory offices, imaging-device manufacturers, and commercial technology partners.
KEY RESPONSIBILITIES:
- Creates and maintains a data dictionary and meta data.
- Supports efforts to ensure that data standards are developed and maintained.
- Ensures that the uses of data through reports and queries are accurate.
- Supports business and system re-engineering and architecture development to define future data needs.
- Serves as an organizational consultant on matters relating to databases by providing expertise to assist users in meeting their needs.
- Performs other related duties as required.
ADDITIONAL RESPONSIBILITIES:
- Ensure that data generated by all OCT and ophthalmic imaging devices are securely transferred, fully backed up, and reliably stored on the laboratory’s network-attached storage servers.
- Develop and maintain a centralized, structured, and searchable master database for all research imaging devices and associated datasets. This platform will serve as the laboratory counterpart to a clinical PACS and will include standardized metadata, naming conventions, documentation, and integrated 3D visualization tools, including technologies developed for Reflectivity.
- Ensure that all OCT and ophthalmic imaging devices are connected to CONTINUUM, the clinical PACS used by the Emory Eye Center. This will require regular communication and coordination with Integrated Ophthalmic Systems, Inc. (https://integratedophthalmic.com/), the company that develops CONTINUUM, as well as with OCT manufacturers and relevant Emory information technology teams.
- Maintain, organize, version, and document all AI models developed by the Eagle-Eye Suite and OEIL, including algorithms for image segmentation, diagnosis, prognosis, and treatment optimization. Documentation should include training and validation datasets, model performance, software dependencies, version history, and deployment status.
- Support the validation, integration, deployment, monitoring, and updating of AI algorithms within CONTINUUM and EPIC.
- Deploy and maintain secure local large language models, as needed, to support data organization and search, technical documentation, AI-model management, clinical reporting, clinician feedback, and related activities.
- Support the clinical evaluation and acceptance of AI algorithms by Emory eye-care clinicians. Develop and maintain a structured survey and feedback system through which clinicians can assess the accuracy, usefulness, interpretability, and clinical relevance of AI outputs.
- Contribute to the patient experience by supporting the near-real-time generation and delivery of validated, AI-assisted imaging reports during visits to the Eagle-Eye Suite, with the goal of making results available within seconds.
- Ensure that all data-management, system-integration, AI-deployment, local-LLM, and clinical-evaluation activities comply with applicable Institutional Review Board protocols, HIPAA requirements, data-use agreements, and Emory policies. This will require regular communication and coordination with relevant Emory departments, information technology teams, and regulatory entities.
MINIMUM QUALIFICATIONS:
- A bachelor's degree and one year of experience in data analysis, statistics, or a related field, OR an equivalent combination of education, training, and experience.
PREFERRED QUALIFICATIONS:
- · Bachelor’s or master’s degree in computer science, data science, biomedical engineering, bioinformatics, software engineering, information systems, or a related field.
- · Experience managing large datasets, servers, network storage, automated backups, and secure data-transfer workflows.
- · Proficiency in Python and SQL, with experience using Linux, relational databases, APIs, and version-control systems such as Git.
- · Familiarity with machine-learning workflows, including dataset and model versioning, validation, deployment, and monitoring.
- · Experience with tools for containerization, AI experiment tracking, and dataset and model versioning is desirable.
- · Familiarity with local large language models, medical imaging, OCT/OCTA, DICOM, PACS, EPIC, or 3D visualization is an asset.
- · Knowledge of data security, HIPAA, Institutional Review Board requirements, and the management of protected health information.
- · Excellent organizational, technical problem-solving, and documentation skills, with the ability to work independently and manage multiple projects.
- · Excellent communication and interpersonal skills, with the ability to coordinate effectively with a broad range of stakeholders, including clinicians, researchers, AI scientists, information technology teams, regulatory offices, device manufacturers, and commercial partners.
NOTE: Position tasks are required to be performed in-person at an Emory University location; working remote is not an option. Emory reserves the right to change this status with notice to employee.