Senior Geospatial Data Scientist - Globally Remote - 12 month fixed term

Our Côte d'Ivoire SDG2 program is aimed at enhancing food security and market resilience in Côte d'Ivoire by leveraging environmental data to support smallholder farmers via the Amini platform. The project focuses on rehabilitating degraded lands, increasing cocoa yields, and promoting sustainable agricultural practices. 

Job Summary: 

Based remotely, the role is for a 12 month fixed term contract

We are seeking a Senior Geospatial Data Scientist with a strong background in machine learning/data science and remote sensing. The ideal candidate should have extensive experience in developing and deploying geospatial and machine learning solutions, particularly in the agriculture sector. You will play a pivotal role in advancing our capabilities to support smallholder farmers and contribute to sustainable agricultural practices. 

Key Responsibilities 

• Develop and implement algorithms that utilize geospatial data to improve the detection and analysis of agricultural activities and conditions, with an emphasis on crop masks, crop health, yield potential, and sustainable agricultural practices. 

• Process ground truth and derived data for model training and validation (e.g. crop types, crop yields, agricultural practices). 

• Train and evaluate machine learning and statistical models to achieve desired performance metrics. 

• Assess the accuracy and quality of large-scale data products such as crop type classifications, soil maps etc. 

• Collaborate with cross-functional teams, including Engineering, to integrate developed models and workflows into production. 

• Communicate technical findings effectively to both technical and non-technical audiences. 

• Contribute to the development of case studies and reports by providing expert insights into agricultural remote sensing products and solutions. 

• Provide technical support and expertise to address customer needs and requirements 

Required Experience and Qualifications 

• Bachelor's degree in geospatial science, environmental studies, data science, computer science, agriculture, or a related field. 

• Proven experience developing statistical, machine learning, or simulation models using satellite imagery and geospatial data. 

• Experience in analyzing and interpreting large-scale geospatial datasets 

• Proficiency with python and open-source geospatial libraries (e.g., GDAL/OGR, xarray, Geopandas, Shapely) and GIS tools like QGIS or ArcGIS. 

• Familiarity with cloud computing platforms (e.g., AWS, GCP) and Linux/Unix environments. 

• Strong ability to translate technical knowledge into accessible insights for team members and customers. 

• Ability to work independently and collaboratively within a globally distributed team. 

Preferred Experience and Qualifications 

• Masters or Ph.D. degree in geospatial science, environmental studies, data science, computer science, agriculture, or a related field.

• At least 3 years of post-academic experience in applied remote sensing to the agricultural sector. 

• Proven experience in utilizing process-based modeling and mechanistic crop models (e.g., APSIM, DNDC) for real-world agricultural problem-solving. 

• Proven experience in building and deploying remote sensing applications for enterprise customers.