Senior Data Manager
About this role
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 algo
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.
Requirements
- 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 algo