Responsibilities
- Partners with scientists, engineers, and community collaborators to curate and coordinate multimodal biomedical datasets.
- Guide researchers through data ingestion into data hubs, support the development of data models and annotations for specialized biomedical data types, and contribute to data governance and workflow design that enable discovery-driven science.
- Applies metadata standards and contributes to improving data management plans across research projects.
- Independently manages datasets and ensures appropriate metadata documentation and lifecycle management.
- Identifies and resolves inconsistencies to validate datasets and metadata and ensure research readiness.
- Applies tools and automation techniques, including AI to improve efficiency of data management tasks such as metadata extraction, validation, and documentation.
- Coordinates with engineering, governance, and scientific teams to implement consistent data standards across projects.
- Provides guidance on data-sharing tools, standards, and best practices for contributors.
Requirements
- 5+ years of experience in biomedical data management/biocuration with a Bachelor’s degree in biomedical research, health informatics, health information management, library science, genomics, neuroscience, or a related discipline.
- Familiarity with biomedical data management/biocuration and an advanced degree (Master’s or PhD) in biomedical research, health informatics, health information management, library science or a related discipline.
- Experience working with complex multi-omic data (e.g., transcriptomics, whole genome sequencing, proteomics, metabolomics, epigenetics, clinical/phenotypic data).
- Experience working on multidisciplinary teams.
- Experience with biomedical data models, metadata harmonization, and ontology development or refinement.
- Experience using project tracking tools such as Jira.
- Familiarity with multiple disease domains (e.g., rare disease, neurodegenerative disease, cancer, immunology).
- Proficiency in data management tools and techniques.
- Strong organizational and time-management skills.
- Clear and effective written and verbal communication skills.
- Demonstrated critical thinking and thoughtful, inclusive technical practices.
- Curiosity about and critical assessment of AI tools to support data management and analysis work.
- Familiarity with using code to manage data and use of version control systems.
Nice to Have
- Familiarity with AWS or other cloud-based resources.
- Experience presenting work to scientific audiences.
Benefits
- Comprehensive medical, dental, vision, life, AD&D, and long-term disability.
- Robust retirement plan and flexible spending accounts (FSA).
- Paid time off and flexible work arrangements.
Additional Information
- Travel is required a minimum of two times per year for on-site events in Seattle, WA.
- Effective verbal and written communication skills.
- Works well in a team and maintains professionalism.
- Follows company policies, procedures, and relevant laws and regulations.
