Agronomic Modeler (Corn)

InnerPlant

Davis (CA)

On-site

USD 125,000 - 175,000

Full time

14 days+
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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

About Us

InnerPlant is on a mission to transform farming as never before imagined: We give crops a voice by turning plants into living sensors that signal the onset of stress, enabling farmers to increase yields and reduce costs by optimizing inputs. We are seeking an Agronomic Modeler to refine and continuously improve the corn disease and pest models behind our commercial product, CropVoice. The CropVoice platform translates signals from our living sensors to pinpoint stress well before visible symptoms, giving farmers and agronomists critical and timely insights and removing the guesswork behind key in-season decisions.

Your Role

As an Agronomic Modeler, you will be accountable for refining the models behind CropVoice's corn recommendations and for making those models accurate, explainable, and reliable for the company, as well as farmers across the Corn Belt. You will work collaboratively with the InnerPlant team to improve our models and explain resulting data and recommendations clearly.

  • Build and maintain statistical and mechanistic models for corn disease and insect pressure, including tar spot, gray leaf spot, southern rust, and key lepidopteran pests.
  • Create and assess the performance of statistical and machine learning models for corn disease risk and spray timing, validating against field observations from our Midwest research network and our plants.
  • Connect model output with InnerPlant's fluorescence detections, weather, and corn phenology to produce field- and zone-level recommendations.
  • Collaborate with other team members to build pipelines for data input and model output.
What Makes You Stand Out

The successful candidate will be a self-starter with a drive for continuous improvement and who works collaboratively and transparently with the team. You will have experience and deep knowledge of modeling in an ecological or biophysical context, including statistical modeling, machine learning, and geostatistics.

  • Relentlessly strive to improve our models, with a focus on improving the accuracy and reliability of models for corn disease and pests.
  • Expertly navigate the relevant technical literature with a view to support modeling capabilities and product needs.
  • Effectively communicate (verbally and in writing) to present your work and relay underlying technical concepts to non-engineers, including agronomists and growers.
Your Qualifications

Bachelor's or Master's degree in a STEM field, PhD preferred. At least 3 years of experience building and deploying relevant models, ideally in industry and/or in a customer-facing context. Knowledge of corn agronomy and corn disease modeling, e.g hybrid disease susceptibility, residue and rotation effects, canopy microclimate, and fungicide modes of action and application windows, is preferred. Software Knowledge: Python, the Python scientific stack, and experience with common development tools and services, such as version control software, package managers, CI/CD pipelines and cloud infrastructure.

The US base salary range for this position is $125,000 - $175,000 + benefits. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. We offer insurance benefits and flexible time off.

InnerPlant provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

InnerPlant provides an amazing opportunity to work on some of the hardest problems facing humanity and help design the agricultural systems of the future. We're backed by John Deere, large farmers, and veteran venture capitalists. WE GIVE CROPS A VOICE www.innerplant.com

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