Overview

We are looking for a Spatial Data Scientist with strong machine learning analytics experience. The position falls under the Spatial Data Science and Applied Learning Lab (SPACIAL) of CIFOR-ICRAF. If you have a background in GIS, spatial data analysis, including remote sensing (satellite data analysis, drone data processing), this position might be for you. You will need a strong background in working on the development and deployment of machine learning models based on remote sensing data (e.g. satellite data). Spatial data science tasks will include data analysis using R Statistics, Python, Julia, and QGIS. A background in the maintenance and use of SpatioTemporal Asset Catalogs (STACs) would be a bonus. Tasks will include identification of data analytics problems, cleaning, and validation of data to ensure accuracy, completeness, and uniformity, and machine learning tasks. The position will support multiple themes and units within CIFOR-ICRAF on scientific project tasks, particularly around access to and use of spatial data, database development and management, report writing, and scientific publications. The position will also supervise junior data scientists, interns, and students.

Summary of responsibilities

• Develop and deploy machine learning models using ground truth and remote sensing data to assess various aspects of ecosystem health at scale based on global datasets. This will include working with both optical and radar data and advanced machine learning frameworks, including deep learning models.
• Conduct spatial data (GIS) analysis tasks using R, Python, Julia, and QGIS.
• Contribute to the maintenance of the SPACIAL STAC.
• Contribute to the development of monitoring systems and platforms.
• Develop and deploy machine learning models using ground truth and remote sensing data. This will include working with both optical and radar data.
• Engage with stakeholders and contribute to the development of trainings for CIFOR-ICRAF staff and outside partners in spatial data analysis using languages such as R, Python and Julia.
• Represent CIFOR-ICRAF at conferences and/or meetings from a technical remote sensing / data science perspective.
• Manage spatial data science fellows and interns.

Requirements

• MSc or PhD in spatial data science, remote sensing, GIS or related field.
• Strong background in machine learning and AI.
• High level of proficiency in computer programming languages such as R, Python, or Julia.
• Experience in handling spatial data.
• Experience with Natural Language Processing (NLP).
• Experience with interactive decision support systems (eg. dashboards).

Personal attributes and competencies:

• Strong English writing and presenting skills.
• Good interpersonal skills.