Note: The job is a remote job and is open to candidates in USA. The University of Wisconsin-Madison is seeking an experienced Data Governance Program Manager to enhance the discoverability, accessibility, integration, stewardship, and responsible sharing of biomedical research data. The successful candidate will lead efforts to establish data governance strategies and work closely with investigators and other partners to support high-quality biomedical research.
Responsibilities
- Lead the development and implementation of a comprehensive biomedical research data governance program across SMPH, including best practices for research data stewardship and lifecycle management
- Partner with investigators to develop and implement data management and sharing plans for grant applications, ensuring alignment with funding agency requirements and FAIR (Findable, Accessible, Interoperable, and Reusable) data principles
- Facilitate the discoverability, documentation, and dissemination of research datasets, including support for assigning persistent identifiers (e.g., DOIs), developing metadata standards, and depositing datasets into institutional and national repositories
- Establish and oversee data quality, data curation, and data stewardship frameworks that promote the accuracy, consistency, completeness, and usability of research data assets
- Lead the design and implementation of data integration, linkage and secure release methodologies spanning structured, semi-structured, textual, imaging, and other heterogeneous biomedical data sources
- Develop processes, standards, and tools that improve interoperability and enable the secure integration of research, clinical, public health, and other data domains to support advanced research initiatives while protecting privacy of patients and participants in research studies
- Guide the development and use of de-identified, limited, and synthetic datasets that support research access while maintaining appropriate safeguards for PHI and compliance with institutional policies
- Develop and implement methodologies for creating research-ready data products that enable reproducible, secure, scalable, and efficient research workflows
- Conduct and oversee data quality assessments, validation activities, and data fitness-for-use evaluations to ensure that research datasets meet established governance and scientific standards
- Serve as a subject matter expert in biomedical data governance, advising investigators, departmental leaders, and research teams on data stewardship, data sharing, metadata standards, and responsible data use
- Develop and deliver training, educational resources, and consultation services that promote best practices in research data management and governance across SMPH
- Monitor emerging trends, technologies, and policies related to biomedical data governance, FAIR data practices, research data ecosystems, interoperability standards, and advanced data management methodologies
- Directly and indirectly supervise staff supporting research data operations, data stewardship programs, data curation activities, and institutional data governance initiatives across SMPH
Skills
- Demonstrable experience with at least three of the following competencies: Research data governance and stewardship frameworks, FAIR data principles and metadata standards, Data integration and entity resolution/data linkage, Research data repositories and data sharing infrastructures, Synthetic data generation and research-ready data products, Data quality assessment and data curation
- Proven experience working on a large, grant-funded project that involves data exchange and sharing
- Familiarity with programming languages such as Python or R, or similar
- Familiarity with: Biomedical and clinical research data management, Multimodal data environments including clinical, genomic, imaging, and unstructured data, and Research informatics and translational science ecosystems
- Excellent problem-solving skills and attention to detail
- Strong communication and collaboration skills
- Experience carrying out research using clinical science or data science with electronic health records
Benefits
- Generous vacation, holidays, and sick leave
- Competitive insurances and savings accounts
- Retirement benefits
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