About Qube Research & Technologies
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating across all liquid asset classes worldwide. We are a technology- and data-driven organization that employs a scientific approach to investing. By combining data, research, technology, and trading expertise, we cultivate a collaborative mindset that empowers us to tackle complex challenges. QRT’s culture of innovation continuously fuels our ambition to deliver high-quality returns for our investors.
Position Overview: Senior Agronomical Engineer (South America Crop Forecasting)
We are seeking a Senior Agronomical Engineer to join our Commodities team in Geneva. This role involves developing and validating proprietary production forecasts for major South American crops, including soybeans, corn, and wheat. As an expert in this field, you will integrate deep regional agronomic knowledge with advanced quantitative data science to support high-value agricultural commodity research and supply modeling.
Your Future Role Within QRT
- Analyze crop development across Brazil, Argentina, Paraguay, and Uruguay, assessing planting progress, phenology, yield formation, pest and disease pressures, and climate risks. Translate field observations into structured yield and production forecasts using statistical and machine learning models.
- Conduct regular field visits to collect ground-truth data, evaluate crop conditions and management practices, maintain regional agronomic networks, and validate satellite-derived indices against observed conditions.
- Integrate multi-resolution satellite and drone imagery with geospatial datasets, applying advanced statistical methods to refine proprietary forecasting models and address structural biases related to crop calendars and double-cropping systems.
Your Present Skillset
- Degrees in Agronomical Engineering and Agronomy (or a related field), with a postgraduate qualification in quantitative data science or analytics.
- Demonstrated professional experience in South American soybean, corn, and/or wheat production systems.
- Experience working with remote sensing and geospatial agricultural datasets.
- Advanced proficiency in Python and applied statistical modeling.
- Ability to independently integrate field agronomy with quantitative forecasting frameworks.
Apply online using the form below. Only applications matching the job profile will be considered.