Digital Agriculture Research Data Manager, Plant Sciences

Digital Agriculture Research Data Manager, Plant Sciences Primary Purpose: The Digital Agriculture Research Data Manager plays a key role in supporting the Nutrien Centre for Digital and Sustainable Agriculture (NCDSA) by facilitating access to high-quality geospatial agricultural and environmental datasets. The position will enable researchers, graduate students, and research assistants to use these data effectively. The position bridges the gap between data infrastructure and research application guiding users in data discovery, analysis, and the application of modern data science and machine learning methods to advance digital agriculture research and innovation. Nature of Work: Reporting to the Director of Nutrien Centre for Digital and Sustainable Agriculture (NCDSA), the Data Manager provides hands-on support to research teams and students working with Earth Observation, agronomic, soil and environmental data. The role focuses on data curation, integration, and applied analytics. The incumbent will work closely with faculty, postdoctoral fellows, as well as graduate and undergraduate student researchers to ensure that Centre datasets are properly organized, documented, and used in compliance with institutional and partner data policies. Work is office-based at the NCDSA, University of Saskatchewan. Collaborates closely with the Data Systems Manager and research staff across the College of Agriculture and Bioresources. Typical Duties or Accountabilities: Research and User Support Guide students and researchers on how to locate, access, and use datasets relevant to their projects. Provide one-on-one and group instruction in geospatial and data-analytic tools (, Google Earth Engine, Python, R, QGIS). Support the application of machine learning and statistical methods to research projects. Develop documentation, training materials, workshops and tutorials to improve research data literacy. Data Curation and Quality Control Organize and document Centre datasets following FAIR as well as Ownership, Control, Access, and Possession (OCAP) data principles. Conduct quality checks, cleaning, and formatting for diverse data sources (, EO imagery, sensor data, yield maps, soil surveys). Maintain metadata catalogues and version tracking for internal and partner datasets. Coordinate data ingestion workflows with the Data Systems Manager. Data Integration and Applied Analysis Assist research teams in integrating ground reference data from field, sensor, and EO data for Centre projects (, soil mapping, MRV, phenotyping). Collaborate on developing reproducible analysis pipelines and dashboards. Ensure that derived datasets and analytical outputs are properly archived and described. Data Governance and Collaboration Ensure that data practices align with USask and partner requirements. Promote ethical, transparent, and sustainable data sharing. Collaborate with the Data Systems Manager to ensure smooth coordination between data users and technical infrastructure. Training and Outreach Deliver short workshops and onboarding sessions for students and visiting researchers. Contribute to the Centre’s educational and outreach activities related to digital agriculture and data science. Provide technical input for data management plans in research proposals and funding applications.  Education: Master’s degree in geoinformatics, data science, agricultural science, or a related field. Experience: Experience with geospatial data, remote sensing, or large agricultural/environmental datasets. Familiarity with machine learning methods (, Random Forest, support vector machine, transformers or similar). Demonstrated experience supporting research or teaching environments. Skills: Proficiency with Python, R, Google Earth Engine, and GIS systems. Excellent organizational skills and attention to data quality. Strong ability to communicate and translate technical methods for diverse users. Understanding of metadata standards and data ethics. Team-oriented approach with ability to collaborate across disciplines. Remove this line if not applicable: