Climate and Environmental Data Scientist at Bioversity International

Key Responsibilities

Under the supervision of the Scientist for Climate Action and the Program Leader of Performance, Innovation and Strategic Analysis for Impact – PISA4I, the appointee will:

• In collaboration with partners of the One CGIAR Initiative on “Informing Sustainable Development pathway with Foresight and Data,” design of climate data cube structure and data models to support the integration of climate variability data.
• Analysis of climate data trends and population of climate data cube(s).
• Development of spatial data models and resultant datasets to support the incorporation of key themes (e.g., Biodiversity, farming systems) into other foresight analyses.
• Contribution to quality assurance and quality control of climate and other related datasets used throughout the project cycle.
• Close collaboration with other team members to support overall foresight activities.
• Contribute to the development of partnerships/collaborations, the writing of project proposals and work plans, to the preparation of workshops.
• Produce scientific papers for peer-reviewed journals and proceedings.
• Represent the Performance, Innovation, and Strategic Analysis for Impact program in key workshops and conferences.
• Supervise short-term consultants or interns working on foresight projects.
• Perform other duties as required.

Qualifications and requirements:

• Ph.D. Degree in Climate modeling; spatial data analytics; niche and species distribution and land use change modeling.
• Deep analytics experience using common open-source tools such as R, Python, and corresponding spatial libraries (e.g. gdal/ogr, terra, sf, rasterio).
• Understanding of CMIP6 climate data structures such as NetCDF and Zarr, as well as familiarity with a variety of climate science related libraries including those used in cloud computing of climate data.
• Experience summarizing climate data trends and climate variability at various spatiotemporal scales using common indices and metrics.
• Expertise in modeling approaches that uses climate and other environmental data as input, such as maxent, random forest, Ecocrop, and in integrating other model results (e.g., crop models) with spatial datasets.
• Familiarity with RS-derived land use and biodiversity datasets, and landscape metrics.
• Excellent command of the English language, both written and spoken.
• Strong analytical and synthesizing skills; ability to think and write clearly and concisely on scientific documents and research proposals.

Desirable qualifications and competencies:

• Experience with interdisciplinary research.
• Peer-reviewed publications
• Strong teamwork, interpersonal, and communications skills; courtesy, tact, and the ability to establish and maintain effective working relationships with people of different cultural and national backgrounds.
• Highly developed skills with personal organization and priority setting.
• Ability to work with a high degree of independence within assigned areas complemented by sound judgment and initiative, and the ability to maintain structured and ad hoc communications with supervisors and colleagues to seek guidance.
• Willingness and enthusiasm to learn and practice new technologies as needed.