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Agriculture Specialist

buscojobs Brasil

Minas Gerais

Teletrabalho

BRL 80.000 - 120.000

Tempo parcial

Hoje
Torna-te num dos primeiros candidatos

Resumo da oferta

A job portal is seeking an Image Annotation Analyst with an agriculture background to annotate datasets and identify crop types. The candidate should have a degree in agriculture and skills in data annotation. This remote role offers flexible hours at a rate of $16 per hour, expected to start this week.

Qualificações

  • Experience in agricultural field studies and data annotation.
  • Prior work with street view imagery of agricultural datasets.

Responsabilidades

  • Annotate agriculture dataset, identifying crop type and stages.
  • Ensure quality, consistency, and accuracy of datasets.

Conhecimentos

Crop classification
Data annotation
Field boundary identification
Knowledge of phenology

Formação académica

Bachelor's / master's degree in agriculture
Descrição da oferta de emprego

We are looking for Image Annotation Analyst having background in Agriculture from Brazil. If you are interested and reside in Brazil, kindly apply to the post on urgent basis as we are anticipating the project to get started this week.

Please find the details below:

  • Project Name: Image Annotation Analyst- Agriculture
  • Hourly Rate: $16 per hour
  • Required Hours: 5-6 hours per day (flexible hours)
  • Project Start Date: This week
  • Location: Brazil
  • Language: local
  • Required Education: Agriculture or agriculture related streams like horticulture, food science etc.

We are looking for an Annotation Analyst to join the team. The ideal candidate will be responsible for annotating agriculture dataset, identifying crop type and stages, ensuring the quality, consistency, and accuracy of datasets. Raters are required to interpret crop types, annotation, and identifying the stages.

Required Skills & Qualifications

  • Bachelor’s / master’s degree in agriculture
  • Experience in agricultural field studies and data annotation.
  • Knowledge of crop classification, phenology (growth stages), and field boundary identification.
  • Prior work with street view imagery of agricultural datasets.
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