General Summary: Anew seeks a GIS professional to support the forest carbon geospatial team in evaluating, executing, and monitoring forest carbon projects, with a focus on forest harvest detection and biomass change quantification. Responsibilities include designing remote sensing models, managing GIS data, producing maps, conducting forest monitoring using remote sensing, and analyzing carbon biomass. The role also involves supporting offset projects, documenting processes, producing marketing materials, and meeting strict deadlines. This is an exciting opportunity to make a significant impact in the forest carbon market.

Primary Responsibilities and Competencies:

Specify remote sensing models to classify forest types, detect forest harvests, and quantify biomass change.
Integrate machine learning and AI methods such as neural networks, deep learning, or support vector machines to improve accuracy and scalability of models and processes
Support mapping and remote sensing efforts for forest carbon offset projects
Collect and synthesize data related to ongoing and planned forest carbon projects
Support modeling of forest carbon projects using ArcGIS, Python, R, or Google Earth Engine
Perform statistical analyses and GIS database management of forest inventories
Draft carbon project modeling documentation
Maintain project timelines and meet strict deadlines
Less than 10% travel is required, primarily to team events and/or conferences

Required Education, Experience and Certification:

At least 2 years of experience in a GIS related occupation
Master’s degree or higher in natural sciences
Experience with application of machine learning algorithms (e.g., Random Forest, XGBoost, etc.) for land cover classification, biomass change estimation, and harvest detection
Proficiency in coding/scripting using R and/or Python and/or Google Earth Engine
Experience in the application of different remote sensing programs
Advanced proficiency with ArcGIS mapping and analysis
Highly self-motivated and has the ability to work both independently and in a collaborative team setting
Strong written and verbal communication skills
Expertise in project management and demonstrated ability to coordinate among various stakeholders
Strong interest in climate change and environmental issues

Preferred Education, Qualifications & Experience:

PhD degree in natural sciences
More than 2 years of experience in a forestry- or natural science related occupation
Demonstrated application of machine learning and AI techniques
Advanced proficiency using Lidar, SAR, and other datasets
Advanced proficiency in forest harvest detection and biomass change models
Familiarity with voluntary/compliance forest carbon protocols in North America
Experience using databases, including experience using SQL (Structured Query Language) to query databases, analyze data, and create reports

Skills:

Advanced programming skills
Advanced Remote Sensing Skills
Experience cleaning and wrangling data
Skilled in spatial analyses
Experience working and communicating in a team environment
Experience producing GIS marketing materials
Highly self-motivated

Remote Scouter