Precision Agriculture Data Scientist - Only On W2

Manager's note:

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.