Join Our Team at Qube Research & Technologies
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes around the world. We leverage technology and data to implement a scientific approach to investing. Our collaborative mindset, shaped by data, research, technology, and trading expertise, enables us to tackle complex challenges. At QRT, a culture of innovation drives our ambition to deliver high-quality returns for our investors.
Position Available: Senior Agronomical Engineer (South America Crop Forecasting)
We are seeking a Senior Agronomical Engineer to join our Commodities team in Geneva. This expert-level role is essential for developing and validating proprietary production forecasts for major South American crops, including soybeans, corn, and wheat. The successful candidate will combine 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 while translating 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. Please note that only applications matching the job profile will be considered.