Data scientist [seeds] – Uberlândia/MG or São Paulo/SP

SP | São Paulo, MG | Minas Gerais
Efetivo (CLT)
Biólogo
Biotecnologista
Engenheiro Agrônomo
Tecnologia da Informação
Tecnólogo em Agronegócio

Responsabilities

• Participation in the development and implementation of global environmental characterization and modeling tools to support product advancement and placement
• Collaborate with regional business and technical stakeholders to drive a data and insight-driven trialing network and product placement strategy
• Knowledge transfer across technical teams, increasing data science fluency within the organization
• Data visualizations to deliver your results and drive business insights, using dashboards and visual analytics tools, such as Power BI, Tableau, R-Shiny, or Qlik Sense.
• Cloud-native model deployment using services such as AWS SageMaker, Azure ML, or GCP Vertex AI.
• Well-documented APIs and microservices for consumption and integration of machine learning outputs.
• Clear technical documentation and reproducible workflows to support research and cross-team collaboration.
• Performance reports and continuous improvement recommendations based on model evaluation and business feedback.
• Effective business storytelling: translate complex analytical results into strategic insights for leadership and functional teams.
• Project impact evaluations to prioritize initiatives and allocate resources efficiently.

Qualifications

• Bachelor’s degree in agronomy, statistics, biotechnology, science and technology, computer science, computer engineering, or related fields.
• Master’s or PhD (preferred) in genetics, quantitative genetics, plant breeding, statistics, bioinformatics, data science or another relevant scientific field.
• Technical Skills:
  • Solid experience in at least one of the following: environmental modelling, machine learning for environmental prediction, quantitative genetics, linear mixed models.
  • Proficient in Python and/or R, experience in ML frameworks is desired. Software version control and best practices using Git is a must.
  • Solid understanding of SQL/NoSQL databases and data engineering principles.
  • Hands-on experience with cloud platforms (AWS, Azure, GCP).
  • Experience using of visualization tools: R Shiny, Power BI, Tableau, Qlik Sense.