Agricultural Scientist

At Halter, we’re on a mission to enable farmers and graziers to run the most productive and sustainable operations. Our customers are using Halter to break free from the time-intensive constraints of conventional practices. Imagine watching 500 cattle stand up and walk calmly towards their next break? No quad bikes,...

We’re backed to deliver on a mission that matters by Tier 1 investors including Founders Fund, Bessemer Venture Partners, BOND, DCVC, Blackbird, Promus Ventures, Rocket Lab’s Peter Beck and Icehouse ventures.

To find out more, visit our LinkedIn & Instagram.

You'll provide agricultural scientific expertise to help shape the next generation of predictive systems for grazing-based agriculture. Working alongside Machine Learning Engineers, Software Engineers and Product Managers, you'll translate agricultural science into innovative products that deliver measurable value to farmers.
You'll identify opportunities where science can improve our understanding of farming systems, design experiments to validate new ideas, and help ensure our predictive models remain biologically meaningful.

Apply agricultural science to improve existing predictive systems and identify opportunities for new products.
Translate biological understanding into hypotheses that can be evaluated through data and machine learning.
Provide scientific guidance during model development, ensuring predictions remain biologically realistic.
Interpret model behaviour and help identify opportunities for improvement.
Design and execute scientific investigations that improve model performance and product capability.
Identify new measurements, datasets and signals that could enhance predictive systems.
Define measurement protocols for capture of validation models, to facilitate training and evaluation of our models
Evaluate emerging agricultural research and assess its applicability to our products.
Contribute to the scientific validation of new modelling approaches.
Partner closely with Machine Learning Engineers throughout the model development lifecycle.
Work with Data Operations to define data requirements and improve dataset quality.
Support Product Managers in evaluating scientific opportunities and trade-offs.
Collaborate with customer-facing teams to understand field observations and convert them into research questions.
Build relationships with external researchers and subject matter experts where appropriate.
During your first several months, success will be measured by your scientific impact and your ability to become a trusted partner to our modelling teams.
Developing a deep understanding of our predictive systems, data pipelines and modelling approaches.
Building trusted relationships across engineering, product and customer teams.
Identifying meaningful opportunities where agricultural science can improve product performance.
Contributing scientific insight that influences modelling decisions and product direction.
Defining valuable new data collection and experimentation opportunities.
Helping establish effective ways of incorporating scientific thinking into our product development process.
MSc or PhD in Agricultural Science, Agronomy, Animal Science, Plant Science or a related discipline.
Significant experience applying agricultural science to solve real-world problems.
Strong understanding of grazing systems and agricultural production.
Experience designing, conducting and interpreting scientific investigations.
Excellent communication skills with the ability to explain complex scientific concepts to multidisciplinary teams.
Ability to influence technical decisions through expertise rather than authority.
Experience working with data science, predictive modelling or machine learning applications.
Experience within agricultural technology or precision agriculture.
Strong quantitative and analytical skills.
Experience working with large datasets to support scientific investigations.
Experience in a commercial technology company or startup.
Scientific publications or recognised technical contributions.
Existing relationships within the agricultural research community.
Experience collaborating with software engineering or product development teams.
Familiarity with remote sensing, sensor technologies or digital agriculture.