Machine Learning Consultant for Smallholder Agriculture
Work on research and software development related to machine learning applications for crop production forecasting
Data modelling
Sub Saharan Africa (remote)
Experience
2-5 years
~2 months ago

Required qualifications:

The successful candidate will work on research and software development related to machine learning applications for crop production forecasting for smallholder agricultural systems at the field to national scales with focus on Sub-saharan Africa. Example projects will involve developing models to map cropland and crop types, forecast crop yields, and alert of impending production shortfalls. These methods will be used to inform key agricultural and food security decisions as well as develop training materials for a range of public and private stakeholders. This research will be carried out through the use of a wide range of satellite data, unique ground-collected datasets, global archives of diverse socio-economic data, and statistics.

  • BS or MS in computer science, remote sensing, GIS, geographical sciences, agricultural sciences, physics, engineering, mathematics, or related fields
  • Strong Python programming background
  • Experience using machine learning libraries such as TensorFlow, Keras, PyTorch, and scikit-learn
  • Experience using remote sensing data and applying geospatial algorithms
  • Interest in agriculture and food security research and applications
  • Strong problem-solving and interpersonal skills; ability to work in a small development team environment
  • Ability to effectively communicate technical concepts to technical and non-technical staff
  • Ability to meet deadlines

Preferred qualifications:

  • Experience with working Google Earth Engine
  • Experience with AWS, Azure, or other cloud computing platforms
  • Experience working with medium to high resolution remote sensing datasets such as Sentinel-2, Sentinel-1, or Planet
  • Experience working with geospatial python libraries such as gdal, rasterio, xarray, and geopandas
  • Knowledge of software design principles and tools (e.g., Github/version control)
  • Publication or scientific writing experience
  • Experience with open source GIS software (e.g., QGIS)