We are DNEXT, commodity agriculture experts. We provide consultancy to a variety of firms involved from the production stage all the way to the consumers and across multiple geographies. We provide our customers with a market intelligence platform hosting the full-scope of datasets related to agriculture commodities.

Our aim is to bring more transparency to the agricultural supply chain for the benefit of the different market stakeholders.

Job Profile

We are looking to hire a senior data scientist with experience in Geospatial data. Your responsibilities will consist of building predictive models for crop yield and overall production using weather and satellite data for all major crops covered by DNEXT. You will join a team of commodity analysts, data scientists and analysts.

Responsibilities

• Design and build machine learning models for crop prediction using Python
• Analyze available weather, satellite and crop production data sets and identify new data sources

Qualifications

• University degree in physics, mathematics, computer science, geospatial Engineering or environmental sciences
• Industry experience in building and deploying machine learning models

Necessary experience:

• Proficiency in Python & Python data processing and machine learning libraries (pandas, xarray, scikit-learn, pytorch, tensorflow, etc.)
• Experience setting up and maintaining relational databases, experience working with spatial database extensions (Postgres)
• Experience in cloud computing, preferably AWS
• High-level written and verbal communication skills
• Ability for teamwork, and capacity to handle short timelines
• Fluent in English

Desired experience:

• Experience working with geospatial data in Python (rasterio, rioxarray, etc.) as well as GIS tools
• Experience building machine learning models using raster or imagery data (convolutional networks, UNET, WNET, etc.)
• Experience using foundation models