Senior Data Manager
DeepHealth
Senior Data Manager
DeepHealth
AI-driven medical imaging and informatics platform
The Senior Data Manager is responsible for owning key data topics across products, including dataset creation, data export, annotation workflows, and performance monitoring, and for driving those topics end to end. This role makes structuring decisions on team tooling and data architecture, builds reusable pipelines and automation, and mentors more junior data team members. Work is done with radiologists, product managers, AI engineers, clinical research scientists, and data engineers to support medical product development.
Essential Duties and Responsibilities
Own one or several data topics across products, such as dataset creation, data export, annotation workflows, and performance monitoring, and drive them end to end.
Design and maintain reusable tooling, including pipelines, dashboards, and automation, for the data team and for stakeholders who need to access, explore, or use the data.
Make structuring decisions on technical implementation, team tooling, and data architecture, and maintain codebase quality and process efficiency.
Surface actionable insights from the data lake by identifying, structuring, and delivering relevant information to product, AI, and clinical stakeholders.
Drive the targeting and collection of relevant data.
Build and structure medically consistent and representative datasets.
Establish annotation guidelines and training so annotation quality stays consistent.
Contribute to ongoing oversight and refinement of AI algorithm performance.
Mentor more junior data team members through technical guidance and knowledge sharing.
Write automated tests and apply code versioning and review standards to data processes and tools.
AI-driven medical imaging and informatics platform
DeepHealth provides AI-powered medical imaging and health informatics solutions that help radiologists analyze X-rays, CTs, and MRIs by automating parts of image interpretation, highlighting areas of concern, and delivering quantitative insights. It works by integrating AI into radiology workflows via cloud-based software, enabling automated image analysis, scoring, and reporting within enterprise imaging systems. The company differentiates itself through its integration with RadNet and strategic acquisitions of iCAD and CIMAR UK, expanding breast imaging capabilities, interoperability, and the scale of its deployments. Its goal is to accelerate the adoption of AI in real-world healthcare, improve diagnostic accuracy and consistency, and streamline imaging workflows across hospitals and health systems.
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