Quantitative Environmental Engineer
- Use a plethora of geospatial data sources (especially satellite imagery and Lidar data) to predict sustainability-related properties over various ecosystems
- Conduct and present uncertainty analysis of Albo’s models
- Develop and implement algorithms for the analysis of spatiotemporal information, as well as change detection algorithms
- Develop and implement methods for downscaling geospatial datasets, as well as geostatistical models for spatial interpolation
- Emphasis on run-time optimization for scaling up the capacity of Albo’s projects
Qualifications
- 5+ years of professional experience as geospatial data scientist, environmental modeler or similar
- MSc in data science, environmental informatics/modeling, remote sensing or other relevant field (PhD advantage)
- Experience working with big spatiotemporal datasets (point cloud, raster and vector), tools (GEE, Python, R, QGIS, ArcGIS, etc.) and environments.
- Experience conducting uncertainty estimations, geostatistical analysis, spatiotemporal interpolation, biogeochemical modeling and/or outlier detection methods (e.g., CCDC, LandTrendR, BFast or similar) will be considered as an advantage
- Ability to write clear, robust and reusable code (preferably Python, Javascript), and document it well
- Great communication and technical writing skills
- Fluent in English
- Teamplayer, positive attitude and care about the environment:)
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Software Development
הפניות מגדילות את סיכוייכם להתראיין פי Albo Climate 2
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קבלת הודעה על משרות חדשות Environmental Engineer ב Tel Aviv District, Israel -. היכנס כדי ליצור התראת עבודה