Precision Agriculture Data Scientist - Only On W2

Key candidate profile

Prioritize candidates from precision agriculture, digital ag, seed companies, agricultural equipment manufacturers, ag retailers, or crop input companies.

Deprioritize

Candidates whose background is primarily academic GIS, remote sensing, crop modeling, research, or general geospatial analytics without hands-on agricultural industry experience.

Critical screening test

The candidate should understand production agriculture and precision-ag data, including how planter performance, seeding rates, sprayer application data, and yield-monitor data relate to one another within a corn-field dataset.

Details

• Person can sit at either Cary or Johnston, but will consider fully remote.
• If remote, would need to be available roughly 8-5 Central time.
• Would also need to be able to travel to Des Moines 1 or 2 times per year.
• 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

Education

• 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.