Engineer Product II - Agronomic Functional Systems
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Role details
Tech stack
Requirements
**We are specifically seeking someone who has worked with agricultural datasets.
Geospatial Analytics background IN THE CONTEXT OF AGRICULTURE is important. We don’t want candidates who are heavy in Geospatial Analytics, but without agricultural background. We are also not seeking a pure agronomist, without the analytics background. This is a good mixture of agronomy and geospatial analytics.
**We need someone with excellent verbal and written communication skills. This person will not just be doing the analytics, but needs to be able to communicate it through Powerpoint slides or PDF summary. Needs to be able to put the material together in an easy to understand and professional way. They won’t be presenting the material themselves, but will need to assemble it together.
We are seeking a technically skilled individual to support data analytics and reporting for marketing initiatives focused on agronomic value of technologies. This individual will work with large agricultural datasets from connected equipment, field trials, remote sensing platforms, and environmental data sources to generate actionable insights for internal stakeholders, dealers, and customers.
The successful candidate will be responsible for managing analytical projects from start to finish, including data processing, statistical analysis, visualization, interpretation, and communication of results. Projects will involve operational datasets (from planters, sprayers, combines, etc), geospatial datasets such as soil maps and satellite imagery, and agronomic datasets including weather, soil, and scouting data.
This position requires someone who can quickly understand project objectives, develop an analytical approach, execute the work, and deliver well-supported recommendations and conclusions.
Technologies used:
Required:
ArcGIS Pro, QGIS, R, Databricks
Nice to have: Operation Center, python, Tableau; PowerBI
A Master’s degree candidate is likely what you will want to target. A PhD could be qualified, but be wary of candidates without any practical experience.
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