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Agronomic Systems Modeling Specialist

ICONMA

Role overview

Qualifications

  • Experience developing, calibrating, validating, and applying APSIM, DSSAT, or comparable process-based crop models for agricultural decision support.
  • Strong understanding of at least one major US row crop production system, with expertise in corn and soybean production preferred.
  • Advanced proficiency in R and/or Python for data analysis, simulation workflows, and model development.
  • Master’s or Ph.D. in agronomy, crop science, soil science, biological systems engineering, agricultural engineering, quantitative genetics, or a closely related discipline.

Responsibilities

  • Develop modeling approaches for G x E x M interactions to predict outcomes in corn, soybean and cotton production systems.
  • Design and execute model calibration, validation, and sensitivity analyses.
  • Collaborate with agronomists, data scientists, software developers, and product managers to build, scale, and communicate outcomes of models.
  • Develop agronomic logic and validation frameworks to ensure AI-generated recommendations are sound and scientifically defensible.

Key facts

Hard skills

Other skills

  • Communication

About the company

ICONMA logo

ICONMA

Management Consulting

We provide Professional Staffing Services & Project-Based Solutions for a broad range of Fortune 500 organizations. ICONMA is a certified Woman-Owned staffing company and was founded in 2000. ICONMA’s corporate headquarters is in Troy, Michigan, and has 15+ locations worldwide. What makes ICONMA stand out in a fiercely competitive industry? *We provide integrated, full lifecycle services across a broad range of business and technical platforms. *No single company can duplicate our full range of staffing and permanent recruiting services nationwide. *Proven track record of attracting and retaining exceedingly skilled professional workers in a highly competitive market. SERVICES OFFERED Staff Augmentation (Contract, Contract to Hire, Direct Hire, Single Source) Data Analysis Project-Based Services & Solutions Hire Train Deploy Service Model Offshore Staff Augmentation Payroll Services AREAS OF EXPERTISE - Information Technology - Engineering - Business Professional - Accounting/Finance - Admin/Clerical/Call Center - Healthcare/Clinical/Scientific - Marketing/Creative mail linkedin@iconma.com Phone (888) 451-2519 Website http://www.iconma.com

Company details

Company typeLarge
IndustryManagement Consulting
Company size1001 - 5000

Links

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Job description

Our Client, an Agriculture Products company, is looking for an Agronomic Systems Modeling Specialist for their Johnston, IA  location.
 
Responsibilities:
  • Develop modeling approaches for G x E x M interactions to predict the outcomes of various management scenarios (planting date, variety selection, fertility management, crop care, etc.) in corn, soybean and cotton production systems across diverse geographies.
  • Design and execute model calibration, validation, and sensitivity analyses to quantify model performance, uncertainty, and limitations across geographies, years, and management systems.
  • Understand interactions among genotype, weather, soil, management, and cropping history to clearly define modeling problems, input requirements, outputs, assumptions, and validation criteria.
  • Work with large, machine-generated agricultural datasets including planter, sprayer, harvest data.
  • Work with large geospatial datasets including soil maps, topography, multispectral imagery, remote sensing products, and environmental data layers.
  • Develop repeatable workflows for processing, summarizing, and visualizing outcomes of these models.
  • Develop agronomic logic, constraints, and validation frameworks that ensure AI-generated recommendations are agronomically sound, transparent, and scientifically defensible.
  • Collaborate with agronomists, data scientists, software developers, and product managers to build, scale, and communicate outcomes of these models.
 
Requirements:
  • Exp. developing, calibrating, validating, and applying APSIM, DSSAT, or comparable process-based crop models for agricultural decision support.
  • Strong understanding of crop physiology, phenology, soil water dynamics, nutrient cycling, and their influence on crop response to management and environment.
  • Strong understanding of at least one major US row crop production system, with expertise in corn and soybean production preferred.
  • Advanced proficiency in R and/or Python for data analysis, simulation workflows, and model development.
  • Exp. working with Databricks, SQL, cloud computing environments, APIs, for scalable analytical and simulation workflows.
  • Demonstrated experience with AI assisted development.
  • Experience working with large multi-environment, multi-year, or multi-management agricultural datasets and developing reproducible analytical workflows.
  • Ability to communicate model assumptions, results, limitations, and uncertainty to both technical and nontechnical audiences.
  • Experience translating scientific models or research outputs into practical decision-support tools, recommendations, or operational workflows for growers.
  • Master’s or Ph.D. in agronomy, crop science, soil science, biological systems engineering, agricultural engineering, quantitative genetics, or a closely related discipline.
  • Preferred Qualifications:
  • Experience with Client Operations Center and precision agriculture technologies including planting, spraying, harvest, automation, sensing, and variable-rate management systems.
  • Familiarity with machine-generated datasets and common grower-facing agronomic data layers (field boundaries, management zones, digital elevation models).
  • Experience working in agricultural industry with agronomic model development.
  • Experience developing agronomic constraints or validation systems for AI-generated recommendations.
  • Experience integrating drone and satellite data into analytics pipelines.
  • Proficiency in SQL, R, Python, Tableau, Power BI, or similar tool
 
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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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