Corn Agronomic Modeler: Disease & Pest Insights

InnerPlant; Davis (CA); On-site; USD 125,000 - 175,000; Full time

Benefits offered by this job

Insurance benefits

Flexible time off

Job summary

InnerPlant is seeking an Agronomic Modeler to refine and enhance the corn disease and pest models behind CropVoice. You will integrate model outputs with fluorescence data, weather, and phenology to guide field-level recommendations for farmers across the Corn Belt.

The ideal candidate has a STEM background with 3+ years of modeling experience, expertise in Python, ML, and geostatistics, and the ability to communicate complex concepts to agronomists and growers.

Qualifications

• Bachelor's or Master's in STEM; PhD preferred.
• Minimum 3 years building and deploying relevant models.
• Knowledge of corn agronomy and corn disease modeling preferred.

Responsibilities

• Build and maintain statistical and mechanistic models for corn disease and insect pressure.
• Connect model output with sensor data, weather and phenology to produce field- and zone-level recommendations.
• Collaborate to build data input and model output pipelines.
• Explain technical concepts clearly to non-engineers, including agronomists and growers.

Skills

Statistical modeling

Machine learning

Geostatistics

Python

Education

Bachelor's or Master's in STEM

PhD preferred

Tools

Git

CI/CD

Cloud infrastructure

Python development stack

Job description

InnerPlant is seeking an Agronomic Modeler to refine and enhance the corn disease and pest models behind CropVoice. You will integrate model outputs with fluorescence data, weather, and phenology to guide field-level recommendations for farmers across the Corn Belt.

The ideal candidate has a STEM background with 3+ years of modeling experience, expertise in Python, ML, and geostatistics, and the ability to communicate complex concepts to agronomists and growers.