Agronomic Data Analyst

About Aerobotics

To date, we've analysed over 340 million trees and 200 million fruit, helping farmers make critical operational and agricultural decisions that maximise yield and efficiency. Our global team of 50+ professionals is headquartered in Cape Town, with commercial offices in the USA, Australia, Portugal, Spain, and South America.

The Opportunity

We're looking for an Agronomic Data Analyst to join our Tech team based in Cape Town. This role serves as a critical bridge between practical farming operations and the dataset creation & management cycle within our machine learning model development. 

Your primary focus will be ensuring data accuracy, rapid development of datasets, and providing on-the-ground insights to improve product development. This means you need to have strong agronomic knowledge combined with technical skills to translate agricultural requirements into quantitative dataset specifications. You'll collaborate closely with product and engineering teams to ensure the agricultural integrity of our data.

What you’ll do

• Review existing datasets and ideate structure/requirements for new product datasets (fruit colour, fruit defect classification, etc.)


• Create and maintain labelling guidelines and quality standards


• Label data and oversee labelers to ensure consistency and accuracy


• Provide agronomic insights to ensure our understanding aligns with farmer understanding and industry standards


• Collaborate with product and engineering teams to translate agricultural requirements into quantitative dataset specifications


• Perform in-field experiments and trials to collect ground-truth data and provide feedback on data collection and user experience


• Utilize in-house labelling tools and progress toward independently training models

What you’ll need

• Bachelor's degree in Agronomy, Agriculture, Crop Science, or related field


• Solid understanding of agricultural principles, crop production, and farming practices


• SQL proficiency for data querying and analysis


• Basic Python programming or demonstrated willingness to learn (preferred)


• Strong organisational skills including attention to detail critical for ensuring data accuracy


• Ability to manage multiple datasets, coordinate with labelers, and maintain clear documentation


• Excellent communication skills to effectively bridge technical and agricultural teams


• Analytical thinking with ability to identify patterns in agricultural data and translate field observations into quantitative insights

Application Process

• Submit your CV & a clear motivation for this role & Aerobotics


• Preliminary virtual interview with our Head of People


• Take home assessment


• Technical Interview with our Head of Engineering


• References & background checks