Senior Remote Sensing Specialist

About us

Acting to combat climate change is one of the world’s most pressing challenges. Climate Friendly was founded in 2003 as a profit-for-purpose business. Our growing team is passionate about active land management, and we are focused on finding economically viable solutions to maximise our impact on climate change. 

 

We are one of Australia’s largest and most experienced carbon farming project developers. This includes more than 160 projects with farmers, plantation managers, agribusiness, and Indigenous groups on carbon farming projects.

 

Climate Friendly has delivered over 20Mt in carbon abatement as at the end of 2020. Our immediate mission is to establish partnerships, by 2025, that will store or reduce 150Mt of CO2-e, while repairing nature and supporting reconciliation. Join our team and you will be helping to build A productive, sustainable land sector that contributes to a zero net emissions & nature positive Australia by 2050

 

We have a genuinely friendly and supportive culture where everyone has a voice and opportunity to help shape our future and to fulfil our purpose.

 

The role

The Senior Remote Sensing Specialist provides technical leadership in designing, implementing, and scaling remote sensing workflows to quantify natural capital metrics at property, regional, and national levels.

 

The role can be based anywhere in Australia, with flexibility to work fully remotely or in a hybrid capacity from home and one of our office locations.

 

Working within the Technology Hub, and in close collaboration with the Science and Innovation team, this role leads the development of scalable systems and tools to transition processes from manual to automated workflows.

 

The Specialist ensures that Climate Friendly’s natural capital reporting is accurate, reproducible, and aligned with defined metrics such as tree cover, ground cover, forage condition, riparian buffers, and listed fauna habitats.

 

The role also supports the development of benchmarking frameworks, integration into external partner systems, and the documentation and standardisation of methodologies to ensure longevity and adaptability as technologies and modelling approaches evolve.

 

Key responsibilities include but are not limited to:

 

• Designing, implementing, and maintaining remote-sensing data workflows to calculate natural capital metrics, ensuring they are scalable and efficient.
• Leading the acquisition, pre-processing, and integration of diverse spatial datasets (e.g., satellite imagery, LiDAR, climate, ecological datasets) for use in natural capital analyses.
• Training, validating, and deploying machine learning models (classification and regression) to predict spatial metrics such as tree crown cover, vegetation condition, and ground cover.
• Designing and executing regional analyses to establish benchmarking quartiles, calibrating outputs using reference datasets (e.g., field survey data) and validating with robust statistical methods.
• Testing property-specific weighting systems for integration into external partner frameworks.
• Collaborating with Data Engineering and Geospatial Engineering teams to define system requirements for ingestion, storage, and automated processing pipelines.
• Establishing and maintaining reproducible research practices, including code versioning, data provenance, workflow documentation, and model performance reporting.
• Preparing technical documentation and procedural guides covering data inputs, methods, and rationale for data and workflow choices.
• Providing mentorship and technical guidance to junior analysts and collaborating across teams to build organisational capability in remote sensing and geospatial modelling.

This position is being offered as a 12-month fixed term contract in the first instance, with the possibility of extension or permanency subject to business needs and performance.

 

About you

 

Essential

• 5+ years’ experience in remote sensing, geospatial analysis, or applied machine learning.
• Strong proficiency in Python and/or R for data science and geospatial workflows.
• Demonstrated expertise with satellite imagery, LiDAR, and large-scale geospatial datasets.
• Strong understanding of ML frameworks (scikit-learn, TensorFlow, PyTorch).
• Skilled in geospatial libraries (e.g., rasterio, geopandas, GDAL).
• Knowledge of projections, coordinate systems, and spatial data standards.

 

Desirable

• Familiarity with Earth Observation Foundation Models for image analysis.
• Experience with Git, Docker, and environment management tools (Conda, uv).
• Strong spatial and temporal data visualisation skills.
• Knowledge of geospatial data infrastructure, servers, or cloud hosting.
• Ability to communicate technical results clearly to technical and non-technical stakeholders
• Experience in managing infrastructure for AI/ML-ops

 

Climate Friendly encourages people from different backgrounds to apply, including Aboriginal and Torres Strait Islander people, people from different cultural backgrounds and people with disabilities.

 

Why join our team?

Our goal is to be seen as an organisation that supports wholeness, lifestyle and wellbeing whilst rewarding individual and collective performance. In addition to competitive salary and transparent career progression opportunities, our benefits include:

 

• Work with purpose, contributing to a productive, sustainable land sector that contributes to a zero net emissions and nature positive Australia by 2050
• A fully hybrid workplace - work to your own rhythm and balance connection and productivity
• A supportive and inclusive environment that promotes diversity
• 2 all staff events a year to connect with your friends and colleagues
• Christmas holiday - 3 days of additional leave each year
• Floating public holidays
• Gender neutral paid parental leave
• 2 days each year for training / development / study leave
• Home office setup and refresh allowance
• Company performance bonus and shared equity