Global Global Head of Carbon Modelling

Imperative is building one of the world’s most ambitious and scientifically rigorous portfolios of nature-based carbon removal projects. Operating across Latin America, Africa, and Asia, we develop large-scale reforestation, mangrove restoration and other ecosystem-restoration project assets under a build–own–operate model—ensuring scientific integrity, operational excellence, and long-term accountability.

We aim to set the global benchmark for quality, transparency, and durability in the markets for nature-based removal credits. Our projects integrate applied field ecology, major-projects project execution capabilities, advanced remote sensing, and state-of-the‑art carbon measurement and modelling to deliver true, infrastructure‑grade removal outcomes.

As our portfolio expands to hundreds of thousands of hectares, we are investing heavily in scientific leadership, data infrastructure, and innovation. This role will be at the centre of that ambition.

OUR VALUES

• Integrity: We act honourably and are guided by a strong moral compass. If things go wrong, we put our hand up, admit it, and adapt.
• Momentum: Speed matters. We have a bias to action. We think quickly, plan tirelessly, mitigate risks, and above all, take action.
• Purpose: We are driven by our desire to make the world better with every interaction, process, and project.
• Accountability: We do what we say and deliver. We seek to be the best at what we do.
• Collaboration: We celebrate diversity of thought, values, and backgrounds, harnessing the strength of our people and partners to achieve more together through teamwork and creativity.
• Tenacity: We are highly ambitious, driven, and hardworking. We persist until we deliver impact.

POSITION PURPOSE

Imperative is seeking a world‑class scientific leader to serve as Head of Carbon Modelling, responsible for the design, calibration, governance, and continuous improvement of the carbon quantification systems that underpin our global NBS portfolio.

This is a mission‑critical executive role reporting to the Chief Carbon Officer. You will architect, build and own Imperative’s carbon modelling frameworks and project‑level models, spanning biomass, soil carbon, growth dynamics, uncertainty quantification, ecological monitoring design, and multi‑source data integration (field, LiDAR, optical, radar, and hyperspectral).

You will help manage and interact with a growing team of modellers, ecologists, biostatisticians, and remote‑sensing specialists and collaborate closely with external researchers, universities, and technical partners. Your work will directly inform carbon production estimations, investment decisions, PDDs, verification outcomes, and the operational design of restoration projects at massive scale.

This is a rare opportunity to shape scientific standards for an entire sector—and to see your modelling frameworks and project‑level models used to restore ecosystems and deliver meaningful, large‑scale climate impact around the world.

KEY RESPONSIBILITIES

1. Scientific Leadership & Architecture

• Own the scientific vision for Imperative’s carbon modelling platform—aboveground biomass, belowground biomass, soil carbon, and ecosystem dynamics across multiple biomes.
• Develop modelling frameworks consistent with IPCC Tier‑3+ expectations and emerging voluntary, jurisdictional and compliance‑grade standards.
• Lead the evolution of model governance: versioning, validation protocols, reproducibility, peer‑review processes, and documentation.
• Serve as Imperative’s top technical authority in carbon quantification, representing the company with Verra, Gold Standard, governments, auditors, technical working groups, and investors.
• Design, calibrate, and implement growth and biomass models (e.g., Chapman‑Richards, Gompertz, logistic, Avrami, Weibull, and Bayesian hierarchical equivalents).
• Develop empirical and model‑based allometric approaches for species‑rich tropical systems, drylands, and mangroves.
• Conduct advanced uncertainty analyses: Monte Carlo, Bayesian methods, bootstrapping, geostatistical models, and error propagation.
• Integrate multi‑source datasets: plot inventory, destructive sampling, soil cores, LiDAR‑derived metrics, optical indices, SAR data, and third‑party geospatial products.
• Produce project‑ and landscape‑scale sequestration estimates that meet or exceed leading scientific and regulatory standards.

3. Data Infrastructure & Workflow Management

• Oversee data ingestion pipelines, QA/QC systems, and the structuring of long‑term ecological datasets.
• Ensure full traceability, reproducibility, and code quality across modelling repositories.
• Work with the remote sensing and field teams to optimise sampling strategies, plot design, and monitoring frameworks.
• Contribute to building Imperative’s next‑generation carbon MRV platform—integrating field data, RS analytics, and model outputs into dynamic digital twins of each project.
• Lead and mentor a distributed technical team.
• Provide technical leadership to project origination, project development, investment committees, and due diligence workflows.
• Guide PDD drafting, validation & verification engagements, and responses to auditor queries.
• Build and maintain academic partnerships with leading institutions and researchers; drive co‑authored publications and external scientific validation.
• Identify key scientific, operational, and modelling risks and lead mitigation frameworks.
• Produce technical briefs, model memos, calibration summaries, and reporting for internal and external audiences.

ESSENTIAL SKILLS & ATTRIBUTES

• Deep expertise in carbon modelling, forest biometrics, ecological statistics, or environmental data science.
• Strong understanding of Verra, AFOLU/IPCC, and jurisdictional methodologies (ARR, mangrove/blue carbon, agroforestry, and grasslands a plus).
• Demonstrated ability to build or lead Tier‑3 frameworks, including:
  • growth curve fitting
  • allometry
  • soil carbon modelling
  • uncertainty quantification
  • hierarchical data structures
• Professional fluency in R and/or Python and experience with reproducible scientific computing.
• Exceptional ability to synthesise complex science into clear recommendations for executives, auditors, and investors.
• Pragmatic, hands‑on mindset—able to move fluidly between high‑level architecture and detailed analysis.

DESIRABLE SKILLS

• Experience with LiDAR, SfM point clouds, biomass calibration using ALS/ULS/HLS datasets.
• Familiarity with SAR data for wetland and mangrove systems.
• Record of scientific publications or contribution to methodology development.
• Leadership experience in cross‑cultural, field‑to‑cloud technical teams.

QUALIFICATIONS & EXPERIENCE

• PhD or MSc in Forestry, Ecology, Biostatistics, Environmental Science, Applied Mathematics, Environmental Engineering, or similar.
• 7+ years of experience in carbon modelling, ecological modelling, remote‑sensing analytics, or a closely related field.
• Demonstrated ability to build, validate, and manage complex modelling frameworks using both field and RS datasets.
• Experience with large, heterogeneous datasets and long‑term monitoring systems.

LOCATION

Global. Preference for Europe/Africa/Middle East time zones.

WHAT WE OFFER

• A career‑defining opportunity: You will architect the modelling backbone of one of the most ambitious restoration portfolios in the world.
• Scientific freedom: Ability to shape frameworks, publish results, collaborate with top researchers, and help set sector‑wide best practice.
• Impact at scale: Your models will directly influence the restoration of millions of trees, thousands of hectares, and entire ecosystems.
• Outstanding colleagues: Work with a highly motivated, mission‑driven, global team combining ecology, data science, engineering, finance, and field operations.
• Competitive compensation: Salary, performance incentives, and potential long‑term value creation through company success.
• Flexibility: Remote‑first work, with field visits encouraged where scientifically relevant.
• Mission & purpose: The chance to apply world‑class science to real climate and biodiversity outcomes.

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