We are seeking an experienced Imaging Informatics Programmer to design, develop, and deploy data-driven solutions supporting imaging operations and analytics. This role sits at the intersection of imaging science, data engineering, and application development, enabling high-quality data collection, monitoring, and reporting across imaging workflows.
Key Responsibilities
Develop and maintain imaging data collection and monitoring systems to support operational tracking and data quality oversight
Design and build databases, including schema design, optimization, indexing, and creation of views and stored procedures
Develop and deploy web-based applications, such as Shiny apps, to enable real-time tracking and visualization of imaging operations
Work with imaging data formats and standards, including DICOM and NIfTI, ensuring proper handling of metadata and headers
Integrate and manage imaging platforms and tools such as PACS, Flywheel, and end-to-end imaging environments
Generate and support operational reports, dashboards, and tracking solutions for imaging workflows
Apply Python-based data science techniques for data manipulation, visualization, and machine learning applications
Collaborate with cross-functional teams to ensure scalable, efficient, and compliant data solutions
Required Skills and Qualifications
Deep expertise in imaging informatics tools and environments, including DICOM, NIfTI, PACS, Flywheel, and related ecosystems
Strong understanding of imaging data structures, metadata, and header information
Experience with database development and administration, including SQL, performance tuning, and data modeling
Proficiency in building data-driven applications using tools such as R Shiny, DataIKU, or similar platforms
Advanced Python skills for data analysis, web frameworks, visualization, and machine learning
Experience developing and maintaining operational reporting and tracking systems
Strong problem-solving skills and ability to work in complex, data-intensive environments
Preferred Qualifications
Experience in clinical or life sciences environments, especially imaging operations
Familiarity with scalable data platforms and cloud-based architectures
Exposure to AI and machine learning workflows in imaging analytics
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