The team at Klim is building the operating system for regenerative agriculture. We help farms restore their soil - and we turn that into real, measurable business value for the food companies, banks and insurers who depend on it.

We’re a Berlin-based agritech startup backed by $22M in Series A funding, partnering with global food leaders such as Nestlé and ADM to build supply chain resilience through regenerative agriculture. Since 2020, we’ve supported +4,000 farmers managing over 900,000 hectares.

Join our incredible team of 80+ dedicated people across Germany, the UK, Poland and Czechia to help build a more sustainable, resilient food system and drive real climate impact.

Klim is seeking an impact-driven Head of Scientific Modelling to lead the scientific backbone of our climate and regenerative agriculture work.

This is a unique opportunity to shape and scale the scientific foundation of Klim's regenerative agriculture programs, making sure our models are not only robust and scalable, but also audit-ready, aligned with leading standards and certification frameworks as well as clients’, farmers’ and strategic requirements.

Your mission

As Head of Scientific Modelling, you will lead the development, integration, and validation of Klim's modelling ecosystem, spanning soil carbon and broader regenerative agricultural impact models. You will lead the development of our core models (RothC and other process-based biogeochemical models) and act as the scientific authority responsible for ensuring consistency and rigour across every scientific model used in the company.

In addition to owning the development and calibration of our core SOC models, you will define and drive an ensemble modelling strategy, integrating multiple models and data sources into a coherent, scientifically robust, and scalable setup. You will ensure that Klim's modelling approach is not only scientifically sound, but also aligned with certification requirements and capable of supporting decision-making across diverse geographies and farming systems, while meeting our customers’ and farmers’ requirements.

This role sits within the MRV team with a strong focus on model integration, validation, and system-level thinking. You will also manage Klim's soil scientists in a matrix organisation, setting technical standards, mentoring on scientific quality, and growing the team's modelling capability over time. You will work closely with product, data, and engineering teams to translate complex modelling approaches into operational, audit-ready workflows.

Your responsibilities

Work with the core model squad, owning the development and application of Soil Organic Carbon (SOC) models (e.g. RothC) and adjacent biogeochemical models that underpin Klim's regenerative agriculture programs.

Strong individual contributor with a hands-on approach, spending a significant portion of the role directly building and delivering models rather than primarily providing oversight.

Provide scientific leadership and management to Klim's soil scientists, setting modelling standards, reviewing scientific work, and developing the team's capabilities.

Ensure scientific consistency across all of Klim's models, so that assumptions, parameterisations, and outputs hang together coherently across SOC, emissions, and farm-system models.

Define and drive an ensemble modelling strategy, leveraging different models and approaches to improve robustness, reduce uncertainty, and ensure consistency across use cases.

Lead the design and implementation of Klim's modelling architecture, integrating multiple models into a unified framework.

Ensure alignment of modelling approaches with certification standards and methodologies (e.g. Verra VM0042/VM0053, ISO 14064/14067, SBTi FLAG, GHG Protocol, and emerging EU CRCF).

Work closely with product and data teams to ensure models support both scientific credibility and operational delivery.

Your profile

Substantial hands-on experience with RothC or other soil organic carbon models, including calibration, parameterisation, and application at scale.