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.

• 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.

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.

• Own the scientific vision for Imperative’s carbon modelling platform—above ground biomass, below ground 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…