Remote Sensing Specialist (Carbon Offsetting) TheRewilding Company is a pioneering organisation dedicated torestoring and enhancing natural ecosystems through innovativerewilding practices. Our mission is to create resilient landscapesthat support biodiversity, combat climate change, and fostersustainable communities. By leveraging cutting-edge technology andscientific research, we aim to revitalize degraded habitats andpromote the reintroduction of native species. As we expand ourefforts globally, we are looking for a Remote Sensing Specialist tojoin our dynamic team, bringing expertise in satellite imagery anddata analysis to help monitor and assess the impact of ourrewilding initiatives. Key words: Biodiversity assessments; Bluecarbon; Carbon credits; Environmental Monitoring; Field Surveys;Forestry; Geospatial Analysis; LiDAR; Mangroves; REDD;Reforestation; Restoration; Sentinel 2. Key details Eligibility:Must have the right to work in the UK Qualifications: PhD in remotesensing and a background in the private sector (candidates with anMSc in remote sensing and strong experience in the private sectorwill also be considered) Working Arrangement: Fully remote Salary:£35,000 - £50,000 (dependent on experience), plus a bonus of 50% ofthe salary if Key Performance Indicators are me Apologies inadvance, but we won't respond to candidates that do not meet theeligibility and qualifications criteria. Key Responsibilities •Lead the innovation and integration of machine learning techniquesto enhance the identification and classification of landcovertypes, ensuring high temporal and spatial resolution using remotesensing data (e.g., Sentinel 2, SAR, JAXA, Landsat imagery) whilefocusing on improving accuracy and reducing uncertainty. •Spearhead the development and deployment of machine learning modelsto monitor and predict both historic and ongoing changes in forestcover for conservation and reforestation projects, optimisingoutcomes through advanced analytics. • Drive the creation ofdynamic, data-driven models that assess the annual risk ofdeforestation over the project lifetime, incorporating digitalterrain models and leveraging predictive machine learningalgorithms to forecast trends. • Lead carbon projection modellingover the project lifetime, utilising state-of-the-art satellitedata, machine learning, and remote sensing techniques to enhancepredictive accuracy. • Innovate and apply cutting-edge remotesensing and machine learning methods to monitor sea-level rise andits impact on project areas, ensuring timely insights fordecision-making. • Develop models using satellite data and machinelearning to determine forest height, soil organic carbon, forestbiomass and tree species at high spatial and temporal resolutions,ensuring a comprehensive analysis of environmental health. •Identify suitable reforestation areas through machinelearning-driven analysis of multi-source satellite and drone data,optimising land-use strategies. • Oversee the processing andanalysis of drone-mounted remote sensing data, such as LiDAR, toenhance understanding of terrain and vegetation structures. • Leadefforts in modelling species zonation using advanced machinelearning techniques to refine ecosystem restoration strategies. •Develop innovative methodologies for utilising remote sensing andmachine learning approaches to baseline and monitor social andbiodiversity impacts. • Collaborate with operational teams tointegrate field data with remote sensing outputs. Essential Skillsand Qualifications: • Master's degree or PhD in Remote Sensing,Geospatial Science, Environmental Science, or a related field, witha proven ability to lead innovation in the application of machinelearning to geospatial analysis. • Extensive experience in remotesensing, GIS applications, and advanced data analytics, with afocus on leveraging machine learning to improve decision-making. •Proficiency in remote sensing software (e.g., ENVI, ERDAS Imagine)and GIS tools (e.g., ArcGIS, QGIS), as well as experience inmachine learning libraries such as TensorFlow or PyTorch. •Demonstrated experience in processing and interpreting satelliteimagery (e.g., Sentinel 2, Landsat) using machine learning and deeplearning algorithms to reduce uncertainty and increase accuracy. •Ability to create commercial-standard data visualisations andcommunicate complex data insights to various audiences, fromtechnical teams to non-expert stakeholders, adapting interpretationmethods accordingly. • Willingness to work within an international,multicultural, remote team. • A commitment to openly share andcollaboratively test work with colleagues throughout every stage ofthe process, fostering a culture of transparency, peer feedback,and continuous improvement. • Strong analytical and leadershipskills, with a track record of driving innovation in remote sensingdata processing and interpretation. • Ability to self-manage andadopt an agile approach to tasks, thriving in fast-paced, startupenvironments where adaptability and self-direction are key. •Proven commitment to staying updated with the latest advancementsin remote sensing, machine learning, and environmental science,with the ability to challenge conventional approaches and fosterboth incremental and transformative change. • Experienceincorporating fieldwork with remote sensing projects, collaboratingwith operational teams on the ground to collect and integrateunderlying data. • Willingness to conduct field work, including toremote regions. • The right to work in the UK. Desired Skills: •Experience with carbon markets, Verra methodologies, and anunderstanding of how machine learning can optimise carbon creditcalculations. • Familiarity with translating workflows into R anddeveloping reproducible machine learning models. • Willingness torelocate to Cornwall, UK; enabling regular in person working withthe CEO and Technical Lead. What We Offer: • £35,000 - £50,000(dependent on experience), plus a bonus of 50% of the salary if KeyPerformance Indicators are met. • Flexible working hours and asupportive remote work environment. • The opportunity to leadimpactful projects that contribute to climate change mitigation andbiodiversity preservation. • Opportunities for professionaldevelopment and growth, with a focus on driving innovation andleading advancements in remote sensing and machine learning. How toApply: • Interested candidates are invited to submit: • CV, focusedon outputs of each role. • A covering letter succinctly evidencingyour fit to the key responsibilities, skills and qualifications. •A short description (no more than 300 words) of how you have driveninnovation in a past project-particularly how you applied newtechnologies, improved efficiency, or solved complex problems. •Applications should be sent to with the title 'Remote SensingSpecialist Application'
