Agricultural Analytics

Important information: To be immediately considered, please send an updated version of your resume to [email protected].

Title: Agronomy Analytics Specialist

Pay Rate: $46 per hour

Location: Johnston, IA OR Cary, NC (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 pers year.)

Duration: 12 months

Type – W2 contract (No C2C)

**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.

About the Role

We are seeking an Agronomy Analytics Specialist to support data analytics and reporting initiatives focused on demonstrating the agronomic value of advanced agricultural technologies. This role is ideal for someone who combines a strong understanding of agriculture and agronomy with hands-on analytical and geospatial data experience.

The successful candidate will work with large agricultural datasets generated from connected farm equipment, field trials, environmental sources, and remote sensing platforms. This individual will transform complex data into actionable insights and professional reports that support internal stakeholders, dealers, and customers.

This is a highly collaborative role requiring both technical expertise and exceptional communication skills. The selected candidate will not only perform analytics but will also create polished PowerPoint presentations and PDF summaries that clearly communicate findings to non-technical audiences.

Important Candidate Profile

We are specifically seeking candidates who possess both:

• Experience working with agricultural datasets and agronomic systems
• Strong analytics and geospatial analysis skills

This is not a fit for:

• Pure GIS or geospatial professionals with no agricultural background
• Pure agronomists without meaningful data analytics experience

The ideal candidate operates at the intersection of Agronomy, Analytics, and Geospatial Data Science.

Key Responsibilities

• Analyze large agricultural datasets from connected farm equipment, field trials, and agronomic research programs.
• Work with operational data generated by planters, sprayers, combines, tractors, and other agricultural equipment.
• Utilize geospatial datasets including soil maps, satellite imagery, and remote sensing data.
• Integrate and analyze weather, scouting, soil, and environmental datasets.
• Manage analytical projects from concept through final delivery.
• Design and execute statistical analyses and modeling approaches.
• Develop data visualizations and analytical summaries.
• Convert technical findings into clear business insights and recommendations.
• Create professional PowerPoint presentations and PDF reports for internal and external stakeholders.
• Collaborate with cross-functional teams to support marketing initiatives and technology evaluations.
• Deliver well-supported conclusions and recommendations with minimal oversight.

Required Qualifications

• Master's degree in Agronomy, Crop Science, Precision Agriculture, Agricultural Engineering, Geospatial Analytics, Data Analytics, Statistics, or a related field preferred.
• Experience working with agricultural, agronomic, or precision agriculture datasets.
• Strong understanding of farming operations, crop production systems, and agricultural technologies.
• Proven experience performing statistical analysis and data interpretation.
• Ability to independently develop analytical approaches and execute projects from start to finish.
• Excellent written and verbal communication skills.
• Strong presentation development and technical reporting abilities.

Required Technical Skills

• ArcGIS Pro
• QGIS
• R
• Databricks

Preferred Skills

• John Deere Operations Center
• Python
• Tableau
• Power BI
• Remote sensing and satellite imagery analysis
• Precision agriculture technologies and equipment data

Ideal Background

Successful candidates may come from backgrounds such as:

• Precision Agriculture Analytics
• Agronomy Research
• Agricultural Data Science
• Crop Science Analytics
• Agricultural Technology Companies
• Seed and Crop Input Organizations
• Farm Equipment Manufacturers
• Agricultural Consulting