Senior Data Manager
Posted Updated
- 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
- 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
- Knowledge of medical imaging and of how data and annotations shape AI algorithm development (required)
- Preferred: Experience with medical device development
- Strong reasoning, attention to detail, and an analytical and scientific mindset (required)
- Ability to manage multiple topics in parallel while maintaining a broader view of product and data priorities (required)
- Ability to structure, document, industrialize, and optimize data processes and tools (required)
- Ability to translate needs between technical and less technical stakeholders and to mentor others (required)
- Experience writing automated tests and working with code versioning and review (required)
- Preferred: Machine learning understanding
- 5+ years of relevant experience in data management, data engineering, or data science, ideally in healthcare or medical imaging (required)
- Master’s degree in a health-related or scientific field (required)
- Excellent proficiency in Python and database query languages, and comfort working with databases such as BigQuery and MongoDB (required)