Agricultural Scientist

About the role

This role centers on applying advanced agricultural science to solve complex problems in grazing management for Halter's growing product suite. The hire will own the scientific integrity of predictive systems used by farmers and graziers operating at scale. You will translate deep biological knowledge into testable hypotheses that directly influence model behavior and product features. A core part of the role involves designing and running experiments that validate new ideas against real-world agricultural data. You will work at the intersection of data science and agronomy, ensuring that machine learning outputs remain biologically plausible and operationally useful. Success depends on your ability to become a trusted scientific partner to engineering and product teams. By joining Halter, you will contribute to a mission that aims to transform an entire industry through technology-enabled grazing practices.

Key facts

What you'll do

• Apply agricultural science to refine existing predictive models and uncover opportunities for new product development.
• Translate complex biological mechanisms into structured hypotheses that can be tested using observational and experimental data.
• Provide rigorous scientific guidance during model development to ensure predictions align with known grazing systems and animal behavior.
• Interpret model outputs to identify scientific inconsistencies and propose targeted improvements.
• Design and execute scientific investigations that measure the impact of new data and features on model performance.
• Identify novel measurements, datasets, and environmental signals that can enhance the accuracy and robustness of predictive systems.
• Define clear measurement protocols for data capture and validation to support model training and evaluation.
• Continuously evaluate emerging agricultural research and assess its relevance and applicability to Halter's product roadmap.
• Contribute to the scientific validation of new modeling approaches through structured experimentation and analysis.
• Partner closely with Machine Learning Engineers to integrate scientific principles across the model development lifecycle.
• Collaborate with Data Operations to define data requirements and drive improvements in dataset quality and usability.
• Support Product Managers by evaluating scientific trade-offs and clarifying the implications of potential product decisions.
• Work with customer-facing teams to capture field observations and convert them into prioritized research questions.
• Build relationships with external researchers and subject matter experts to incorporate best-in-class scientific thinking.

Requirements

• Hold an MSc or PhD in Agricultural Science, Agronomy, Animal Science, Plant Science, or a closely related discipline.
• Demonstrate a strong foundational understanding of pasture-based livestock systems and associated management practices.
• Show evidence of analytical thinking and problem-solving skills applied to agricultural or biological data.
• Communicate effectively in written and verbal form to convey scientific concepts to both technical and non-technical audiences.
• Have experience working with data-driven projects where experimental design and validation are essential.
• Exhibit strong attention to detail and the ability to manage multiple scientific inquiries simultaneously.
• Be committed to maintaining scientific rigor in all aspects of model development and hypothesis testing.
• Possess the right to work in New Zealand or eligibility to obtain residency without restriction.

Nice to have

• Experience working with machine learning pipelines or data-intensive software development.
• Familiarity with livestock behavior, grazing ecology, or pasture physiology.
• Prior involvement in agricultural research that led to published outcomes or field trials.
• Knowledge of data visualization techniques for communicating scientific results to diverse audiences.

Practical notes

• This is a full-time position based in Auckland.
• Candidates must meet all eligibility and requirement criteria as stated.
• No partial or fractional work arrangements are available for this role.
• There are no relocation allowances or visa sponsorship provided at this time.
• Applicants are advised to apply only if they can meet the stated requirements without exception.
• The position is subject to change based on evolving business and scientific priorities.
• Successful candidates will be required to complete any necessary background checks as part of the hiring process.