Modeling Scientist

Department: Science / Modeling & Data Analytics

Reports to: Lead Modeling Scientist / Chief Machine Learning Architect

Location: Remote

Base Salary Range: $75,000 to $130,000 annually

 

General Position Description

The Modeling Scientist plays a central role in advancing and scaling Arva’s platform for monitoring, reporting, and verifying (MRV) greenhouse gas emission reductions and removals. This role is a part of the multidisciplinary Sciences team, this role combines expertise in ecosystem science, modeling, machine learning, and data science, working to advance our MRV platform to make regenerative agriculture the standard, enriching lives and restoring the planet.

 

In this role, you will customize and improve the application of ecosystem biogeochemical models like DayCent and MEMS to analyze greenhouse gas emissions, nutrient cycling, ecosystem resilience, crop growth, and soil processes in agricultural and rangeland systems. You will be responsible for writing production-grade code, prototyping model workflows, and building computational pipelines that enable model calibration and validation, data-model integration, and uncertainty quantification. This position offers the opportunity to shape the scientific foundation of a platform designed to accelerate the global transition to regenerative agriculture. By contributing to modeling innovation and scalable data solutions, you’ll help make regenerative practices the standard while enriching lives, supporting producers, and restoring the planet for generations to come.

 

Primary Job Responsibilities

• Develop and maintain code to support ecosystem biogeochemical model workflows, including data-model integration, parameter optimization, and uncertainty quantification. 
• Design and implement pipelines for collecting, processing, and integrating datasets relevant to ecosystem modeling in croplands and rangelands.
• Write clean, modular, and well-documented code to support reproducible and scalable modeling workflows.
• Analyze model outputs, troubleshoot discrepancies, and generate approaches to improve model performance.
• Interpret and evaluate model predictions to assess the impacts of different regenerative practices on ecosystem services and resilience.
• Collaborate with internal stakeholders (sales, product, operation teams) to ensure scientific integrity and usability of model results.
• Document workflows and communicate findings through technical reports, scientific publications, and presentations to stakeholders, including internal teams, clients, and academic communities.
• Stay current with greenhouse gas accounting guidelines and protocols, modeling advancements, and ecosystem science to generate innovative, science-driven modeling strategies.  

 

Key Competencies / Requirements

• MS or PhD in Environmental Science, Ecology, Biology, Agriculture or a related field.
• Advanced proficiency in scientific and technical programming using Python, GitHub, and Docker, with experience writing modular, testable, and sharable code.
• Experience working with large datasets and building reproducible model pipelines.
• Demonstrated expertise in ecosystem biogeochemical models, particularly with models like DayCent, MEMS, or similar.
• Familiarity with cloud platforms (AWS, Azure, etc.) and relational or spatial databases (PostgreSQL, geodatabases).
• Proficient in data analysis and statistical methods with the ability to communicate technical topics clearly to diverse audiences both written and verbal.
• Ability to work collaboratively in a multidisciplinary team environment.
• Commitment to promoting regenerative agricultural practices with scientific integrity.

 

Preferred Qualifications

• PhD in a relevant field.
• Experience integrating machine learning or statistical techniques into modeling pipelines.
• Experience with GIS and remote sensing technologies.

Compensation, Perks & Incentives:

• Competitive base salary 
• Annual performance-based bonus
• 401 K Employer contribution
• 100% Employer paid health insurance for employee and family
• Stock options

Employment Eligibility

Only applicants currently eligible to work in the United States will be considered for this position. 

 

About Arva Intelligence

Arva is a machine learning software-based SaaS company with offices located in Houston, TX and Park City, UT. Arva's platform was built to apply our novel ML technology to the agricultural industry, optimizing and measuring regenerative practices, improving crop yields, and reducing operational costs for producers. Our platform helps our customers and partners capitalize on "natural regenerative practices" by providing recommendations that improve environmental and ecological ecosystems. Platform features include practice verification and registration, as well as the sale of environmental asset credits to our corporate buyers. Thus, Arva is helping to keep the planet green by providing a "green-tech" platform that informs, measures, validates, predicts, and registers carbon exchange opportunities, allowing growers and ranchers to produce and sell credits that are bought by our corporate partners, who endorse sustainable food supply and carbon neutrality. 

This job description reflects the core duties of the role but is not intended to be all-inclusive. The role may evolve as the company grows, requiring additional responsibilities or changes in scope.