Remote Sensing Analyst

2h2 hours ago

Revalue Nature

ID · Full-time

About this role

Revalue exists to deliver a fundamental step-change in the quality and integrity of carbon projects by rethinking projects from the ground up. Revalue Nature has raised $10 million in Series A funding co-led by Ecosystem Integrity Fund and SJF Ventures. Join us to supercharge nature-based developers and protect nature at scale.

Revalue supercharges leading nature-based carbon project developers with technical support and financing from initial assessment to carbon credits issuance. This is underpinned by proprietary tech for accuracy, speed, automation, and insights. The Remote Sensing Analyst reports to the ML-RS Lead in the Data Intelligence Team.

Our global, diverse team spans time zones with a track-record of high-impact carbon projects in iconic landscapes. We partner with leaders in nature conservation and restoration. This full-time remote position is based in Indonesia.

We offer opportunities to do the best work of your life while focusing on balance outside work. Build long-term partnerships and contribute to planetary-scale impact. Stay at the forefront of remote sensing advancements.

Requirements

Master's degree in Remote Sensing, Geography, Environmental Science and Geoinformatics, or related field.
Experience in remote sensing data analysis, particularly in land cover change detection and classification, using radar, optical sensors (e.g. Landsat and Sentinel), and high-resolution imagery.
Familiarity with machine learning techniques, statistical analysis, and their application in remote sensing.
Knowledge of GIS software such as ArcGIS, QGIS, or Google Earth Engine and geodatabases.
Strong programming skills in Python and experience with machine learning libraries such as Scikit-Learn, Geopandas, Rasterio and GDAL.
Experience working with cloud-based computing environments e.g. GCP, AWS.

Responsibilities

Design, develop, and implement remote sensing projects and methodologies to collect, analyse, and interpret spatial data.
Develop, implement, and evaluate remote sensing algorithms and machine learning models for land cover change detection and land use classification using radar, optical sensors, and high-resolution imagery.
Collaborate with interdisciplinary teams to integrate remote sensing data with other data sources and contribute to comprehensive analyses and model development.
Develop and maintain documentation of code, methods, and results for transparency and reproducibility.
Stay up to date with advancements in remote sensing technologies and methodologies and recommend improvements to data collection and analysis processes.