Senior Geospatial Data Scientist

Radiant Earth Foundation’s core mission is to make insights from remote sensing data and machine learning an order of magnitude more accessible for global non-profits, humanitarian organizations, and companies and governments in emerging economies.

We do this by curating, hosting, and listing/redirecting to open training datasets and models through Radiant MLHub. MLHub is a repository and registry of geospatial training data and models, and we lead community efforts to develop standards and increase interoperability of these data for machine learning applications.

In addition to training data catalogs, we work with organizations on complex use cases with high-impact outcomes. Since our founding in 2016, we’ve worked with Bill and Melinda Gates Foundation (a founding funder) and Omidyar Network (another founding funder), as well as NASA, GIZ, Schmidt Futures, McGovern Foundation, Digital Earth Africa, CGIAR, and more.

We are searching for a passionate and experienced Senior Geospatial Data Scientist to build novel machine learning models for various applications using Earth observations and lead our ML projects portfolio including but not limited to generating new training datasets, organizing competitions, and developing training and capacity development programs.

Our team is currently distributed across the US and Nigeria and you will be working remotely within the US.

What You Will Do:

• Build machine learning models for various applications in agriculture, land monitoring, and infrastructure mapping.
• Lead the design of competitions based on Radiant MLHub datasets.
• Prepare tutorials and training materials for machine learning applications using datasets and models on Radiant MLHub.
• Work closely with Engineering Lead and Technical Project Manager to lead machine learning projects.
• Develop and propose new project ideas for the Company to pursue.

Basic Qualifications:

• +3 yrs of experience in geospatial machine learning projects.
• Bachelor’s or Master’s degree in Computer Science, Environmental Science, Remote Sensing or relevant field.
• Experienced in Python and Jupyter Notebooks.
• Experienced in SQL.
• Deep knowledge of and experience in using machine learning techniques.
• General knowledge of geospatial and remote sensing data.
• Experienced working with machine learning libraries such as PyTorch or TensorFlow.
• Working knowledge of geospatial packages (GDAL, Shapely, GeoPandas, rasterio).
• Experience in data visualization in Python.
• Experience with version-control platforms (e.g. GitHub, GitLab).
• Excellent communication and team collaboration skills.
• You are passionate about the world's challenging problems, and eager to help address them.
• Eligible to work in the US (visa sponsorship is not provided).

Preferred Qualifications:

• Experience leading machine learning projects.
• Familiarity with SpatioTemporal Asset Catalog (STAC).
• Experience working in a commercial cloud environment (Azure or AWS).

What we offer:

Radiant Earth offers a competitive salary and attractive benefits package with flexible time off. We work with a diverse user community, and you will have the opportunity to work on highly impactful projects. We have a collaborative work environment with a robust support system driven by passionate individuals.

While we sincerely appreciate all applications, only those candidates selected for an interview will be contacted. All applications are considered confidential. Radiant Earth Foundation is an equal opportunity employer.