✨ About The Role
- The role involves developing new vegetation intelligence products using standard geospatial Python libraries and machine learning tools.
- Responsibilities include supporting existing products through data exploration, model improvements, and bug fixes, particularly using QGIS, Dagster, Sentry, and Grafana.
- The candidate will represent the team by leading projects and initiatives, ensuring clear communication of the value of contributions to stakeholders.
- Building tooling and processes to measure the value and performance of contributions is a key aspect of the job.
- The position requires collaboration with cross-functional teams, including product, design, engineering, and platform members throughout the scientific product lifecycle.
âš¡ Requirements
- At least 8 years of commercial experience as a Data Scientist or Machine Learning Engineer is required.
- Advanced scientific Python experience, including proficiency in libraries such as numpy, scipy, scikit-learn, and pandas, is essential.
- Candidates should have experience with geospatial or satellite data, utilizing tools like gdal, rasterio, shapely, fiona, geopandas, and QGIS.
- Familiarity with deep learning algorithms, particularly in the context of geospatial data, and experience with frameworks such as pytorch and tensorflow are important.
- A passion for climate-related issues and a desire to work in a fast-paced, remote-first environment are crucial for success in this role.