Analyst III, Data Science & Remote Sensing in at American Forest Foundation

Description:

Closing Date: Monday, September 28, 2026

About us:

The American Forest Foundation (AFF) unlocks the power of family forests as a climate solution while helping thousands of landowners care for their land and improve forest health. Through its Family Forest Carbon Program, AFF expands access to the voluntary carbon market for family forest owners from all walks of life while producing high-quality forest carbon credits to help companies reach their net zero goals. The organization’s strategic direction seeks to enable family forests to capture and store one billion tonnes of carbon by 2050.
We do not do this alone. AFF works across a broad coalition of conservation partners, corporations, and policymakers to equip family forest owners with financial and technical support to implement sustainable forest management practices on their lands and activate their forests as a critical tool in the fight against climate change.
AFF is in a mode of complex problem solving and rapid iteration. All teams at AFF are working to discover solutions to the planet’s most pressing climate issues through developing and iterating viable and scalable models for impact. AFF is driven by values of our shared purpose, measurable and verifiable results, and learning for continuous improvement to tackle big conservation challenges.

About the Role:

The Analyst III, Data Science & Remote Sensing serves as a key scientific and technical contributor within AFF's Science team, supporting the design and execution of analytical projects that support forest-climate program implementation, methodology development, conservation impact measurement, and strategic research initiatives. This role offers an opportunity to contribute to the scientific analyses that support one of the largest forest carbon programs in the United States with influence shaping applied forest carbon accounting approaches globally.

In this role, your work will directly inform how millions of acres of family-owned forests are valued for climate impact. The analyses, methods, and scientific innovations you develop will influence conservation outcomes, carbon market integrity, and the long-term stewardship of forests across the United States, in addition to influencing the continuous improvement of the science underpinning carbon projects globally.

This role is intended for an experienced data analyst who can develop and execute quantitative analyses independently and in collaboration with AFF scientists and partners. The successful candidate will combine expertise in statistics, data science, remote sensing, geospatial analysis, and scientific programming to address complex questions related to forest carbon accounting, carbon forecasting, permanence and durability, leakage assessment, remote sensing-based monitoring, and conservation outcomes.

The position will support AFF's scientific leadership through analytical innovation, technical reports, presentations, partner collaboration, and applied research projects. The analyst will be expected to produce decision-ready analyses, identify methodological improvements, evaluate novel data sources and technologies, and communicate complex findings effectively to technical and non-technical audiences.

This is an ideal opportunity for an individual who thrives in a mission-driven environment and enjoys translating cutting-edge science into practical solutions that support climate, conservation, and family forest landowners.

Responsibilities:

• Conduct the design, execution, validation, and documentation of advanced statistical, geospatial, and remote sensing analyses supporting AFF's scientific and programmatic priorities.
• Develop reproducible analytical workflows and production-quality code in R and related scientific computing environments.
• Conduct analyses to inform development and refinement of approaches used by AFF and wider market integrity initiatives, including but not limited to baseline development, leakage assessment, and permanence and durability.
• Integrate and analyze large, complex datasets from remote sensing platforms, field inventories, program operations, environmental datasets, and literature.
• Evaluate emerging technologies, including machine learning and AI, for potential integration into scientific workflows and monitoring systems.
• Collaborate closely with scientists, program staff, and external partners to translate business and scientific questions into rigorous analytical approaches.
• Document and communicate analytical methods, assumptions, uncertainties, and findings clearly to audiences ranging from technical experts to organizational leadership, enabling quality assurance, transparency, and reproducibility.
• Contribute within AFF's science chapter, identifying opportunities for innovation, efficiency, and scientific advancement across AFF’s strategic priorities.

Requirements:

Candidate requirements:

• Advanced degree (M.S. or Ph.D. preferred) in forestry, ecology, natural resources, environmental science, statistics, geography, remote sensing, data science, or a related quantitative discipline.
• Minimum 3-6 years of professional or postdoctoral experience conducting advanced quantitative analyses in environmental, natural resource, climate, forestry, conservation, or related sectors.
• Demonstrated and strong proficiency in R, Python, or equivalent scientific computing environments for statistical analysis, reproducible workflows, and scientific programming.
• Strong foundation in statistical modeling, predictive analytics, uncertainty quantification, and applied data science.
• Experience working with large geospatial and remote sensing datasets.
• Demonstrated expertise using GIS and spatial analysis tools.
• Experience developing and maintaining reproducible analytical workflows and well-documented codebases.
• Experience designing analytical approaches to answer complex scientific or operational questions.
• Strong technical writing skills, including development of scientific reports, methodologies, peer-reviewed manuscripts, or technical documentation.
• Demonstrated ability to communicate complex analytical results to both technical and non-technical audiences.
• Experience collaborating across multidisciplinary teams and managing multiple concurrent projects.
• Experience working with cloud-based analytical environments (AWS, Azure, Google Earth Engine, or equivalent).
• Preferred:
• Experience with forest carbon accounting, carbon markets, forest inventory analysis, or ecosystem modeling.
• Experience with machine learning, AI-enabled analytical workflows, or predictive modeling applications.
• Experience with carbon standards, environmental methodologies, or scientific validation processes.
• Publications in peer-reviewed scientific literature.

Core Competencies:

• Agility (Level 2) – Thriving in volatile, uncertain, complex and ambiguous environments by anticipating and responding to changes with swift, focused and flexible actions.
• Collaborating with Others (Level 3) – Working together with others in a cooperative and supportive manner to achieve shared goals.
• Ensuring Accountability (Level 2) – Holding yourself and others to high standards of accountability, creating an infrastructure and transparent organization culture that supports and measures personal and organizational responsibility and accountability.
• Problem Solving (Level 4) – Identifying problems and the solutions to them. Your contributions and leadership will be appreciated. Our staff is passionate, dedicated and good at what they do, and will be deeply grateful for your efforts to create and preserve an environment that is both fun and fair.

Job Function Competencies:

• Data Literacy (Level 4) – Using data to gain insights, solve problems, and inform decisions.
• Scientific Rigor (Level 3) – Ability to design and implement methods that withstand peer and market scrutiny.
• Machine Learning and Artificial Intelligence (Level 3) – Processing data from various dimensions in order to provide quick insights and develop innovative or automated machine learning modelling algorithms or solutions.
• Data Visualization and Presentation (Level 2) – Creating compelling visual narratives to present the findings of data analyses.

What’s attractive to the right candidate:

• You have the unique and exciting opportunity to work with amazing colleagues, partners and landowners to help connect forest landowners with technical and financial assistance to better steward their land and achieve vital landscape-scale conservation impacts.
• Your contributions and leadership will be appreciated. Our staff is passionate, dedicated and good at what they do, and will be deeply grateful for your efforts to create and preserve an environment that is both fun and fair.
• We offer a flexible work environment that respects your life outside of work.
• Salary is commensurate with experience.
• AFF offers a comprehensive and competitive benefits package.

Contact us to apply:

We welcome candidates from academic, nonprofit, government, consulting, and industry backgrounds, including recent PhD graduates and early-career scientists seeking to apply quantitative research skills to real-world climate and conservation challenges.

We know there are great candidates who may not check all these boxes, and we also know you might bring important skills that we haven’t considered. If that applies to you, don’t hesitate to apply and tell us about yourself.

We are committed to creating a diverse work environment and proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status or any other basis protected by law.