23 set - Brindisi
XML International
We are looking for an experienced GeoAI Data Scientist to support geospatial analysis for humanitarian and disaster-response operations within a major international organisation.
This is a hands‑on role at the intersection of Geospatial AI, Remote Sensing, Earth Observation and Data Science , focused on turning complex spatial data into reliable information that can support real‑world operational decisions.
What You’ll Work On
- Build and maintain automated geospatial data pipelines using Python .
- Analyse satellite imagery and raster, vector and environmental datasets.
- Work with SAR and optical Earth Observation data .
- Develop and apply geospatial machine-learning approaches to flood risk, damage assessment, change detection and related operational challenges.
- Evaluate model performance and underlying data quality.
- Investigate false positives and validate analytical outputs.
- Clearly communicate model uncertainty, limitations and appropriate use.
- Translate complex geospatial analysis into actionable information for operational teams.
- Collaborate with technical specialists across geospatial, data and operational functions.
What We’re Looking For
- Practical experience with GIS and geospatial data processing.
- Experience working with raster, vector and/or environmental datasets.
- Experience developing or maintaining an automated geospatial workflow , from data ingestion through processing to usable outputs.
- Experience applying Machine Learning to geospatial problems .
- Strong understanding of model validation and data quality.
- Ability to investigate false positives and explain model uncertainty and limitations.
- Strong communication skills with both technical and non-technical stakeholders.
- Fluent professional English.
- Ability to work on-site in Brindisi, Italy .
Particularly Valuable
- Flood mapping or flood-risk analysis
- Humanitarian or disaster-response applications
Interested?
You do not need experience in every area listed above. We welcome candidates with strong, transferable geospatial skills and the ability to apply them to new operational challenges.
If you combine Python, Remote Sensing, GIS and geospatial Machine Learning and enjoy turning complex Earth Observation data into information people can actually use, we’d like to hear from you.
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