We at Yara are part of a global network, collaborating to profitably solve some of the world's key challenges - resource scarcity, food insecurity and environmental change.

Agronomic Modeling Specialist

Sobre Nossa Unidade

Yara is one of the world’s leading manufacturers of fertilizers and plant nutrition solutions. Our mission is to feed the world a responsible and sustainable way.

The Yara Digital team with locations in Europe, Brazil, Singapore, and North America builds and designs digital solutions to help farmers globally use our products more efficiently and to improve the ecological footprint by creating business models that make our products more accessible.

We build solutions for farmers, construct hardware and sensors, crunch satellite data, apply artificial intelligence, and turn research results into solutions. Our teams is made of designers, software engineers, hardware developers, data scientists, solution managers and product owners.


  • Serve as an expert in model principles and practice;
  • Serve as an expert in regional agro-ecosystems and agricultural practices;
  • Gather and organize data from primary sources to calibrate the model in the region;
  • Work with other modelers and data analysts to validate the model for the region;
  • Work with users and customer support personnel to help explain model results to agronomists and customers;
  • Troubleshoot model errors or unexpected results;
  • Participate in defining, testing, and gathering feedback on features per customer requests and business goals.


  • BS or equivalent in agriculture or related field and experience with growers and/or collecting and analyzing field data.
  • MS or higher in agriculture or related field.
  • Expert level understanding of environmental processes (especially soil-water processes and nutrient cycling).
  • Familiarity with the region (Brazil) and its soils, climate, and agricultural systems.
  • Excellent analytical skills and problem solving.
  • Familiarity with scientific literature and experimental best practices in agriculture.
  • Strong statistical analysis skills (Highly beneficial).
  • Experience with environmental or biogeochemical models (Highly beneficial).
  • English (fluent).

Informações Adicionais

An environment that seeks to value differences and is open to receive people with any disabilities, gender, ethnicity, sexual orientation and different mindsets.