Climate Data Scientist, Sustainability

The core mission is to own the scientific integrity of Watershed's built-in sustainability methodologies. Concretely, this means translating the GHG Protocol, sector-specific guidance and emerging regulatory requirements, including CSRD and ESRS, into product logic that is rigorous, auditable and usable by non-specialist customers. The role sits at the intersection of science and software, so the work is not abstract research: every decision feeds directly into features that companies use to compile inventories and disclosures. Beyond maintaining existing methodologies, the Climate Data Scientist will investigate complex customer and product questions where accounting rules, data quality and business context collide. Expect to develop pragmatic approaches for messy real-world data, write technical specifications, review code implementations and help build tests that give confidence in scientific correctness. You will also contribute to internal methodology standards and document the reasoning behind choices so that auditors and verifiers can follow the trail. A significant part of the role is collaborative translation: working with go-to-market and customer-facing teams to explain methodology choices clearly, and helping shape how Watershed's platform evolves as standards and scientific consensus shift.

This role offers unusually deep exposure to the machinery of corporate carbon accounting. You will gain hands-on mastery of the GHG Protocol Corporate Standard and Scope 3 Standard, and likely develop working fluency in emerging frameworks such as the Land Sector and Removals Guidance and updated ESRS. Because the work is embedded in a product, you will also learn how standards become software, how methodological choices are tested, versioned and defended under audit. The technical learning curve is real but supported. You are not expected to be a software engineer, yet you will grow comfortable reading Python, reasoning about implementation details and contributing configuration or logic. Exposure to assurance and audit processes for GHG inventories is another likely gain, as is familiarity with LCA models, emissions factor datasets and sustainability software architecture. Mentorship comes through close collaboration with software engineers, data scientists and product managers, plus the Methodology team's internal review culture. For someone with a scientific background, this is a rare chance to translate academic expertise into production-grade capabilities used by large enterprises.

The ideal candidate holds a Master's or PhD in climate science, environmental science, sustainability, industrial ecology or another quantitative field, backed by at least five years in corporate sustainability, carbon accounting, sustainability consulting or climate strategy, ideally with large, complex organisations. They combine scientific depth with product instincts: they understand not just the science of sustainability but how it behaves when applied across sectors, data realities and regulatory contexts. Technically, they know the GHG Protocol Corporate Standard and Scope 3 Standard in depth, including the reasoning behind the rules, not just the rules themselves. They can read and reason about a Python codebase and are comfortable contributing where appropriate. Familiarity with assurance processes, LCA modelling, emissions factor datasets or sustainability software is a strong bonus. Soft skills matter enormously here. The role demands a systems thinker who can zoom out to see interconnected business and sustainability systems and zoom in to find high-leverage technical solutions. Clear communication to audiences ranging from academics and auditors to engineers and customers is non-negotiable, as is a pragmatic temperament for messy data and competing priorities.

Watershed is a product-building company, so the strongest applications will show that you can move between scientific rigour and operational pragmatism. Rather than listing methodologies you know, describe a specific instance where you translated a standard (say, a Scope 3 category boundary question) into something a team could act on. Concrete examples of working with messy corporate data, defending methodological choices to auditors, or collaborating with engineers will land far better than general sustainability credentials. Because the Methodology team sits between science and software, it is worth addressing the technical dimension directly. You do not need to be an engineer, but you should demonstrate comfort with code and data: a project where you scripted analysis in Python, reviewed an implementation, or wrote a technical specification is highly relevant. If you have worked on carbon accounting methodologies, emissions factor datasets or LCA models, make that visible early: it is explicitly listed as a bonus for good reason. Finally, tailor your materials to Watershed's position as a platform rather than a consultancy. Show that you understand why auditable, scalable data matters to enterprise customers facing CSRD and investor scrutiny. Prepare to discuss how you would handle a real methodological trade-off, and be ready for a process that starts with conversations about your experience and interests before deeper skill interviews.

The role sits at the heart of Watershed's mission: enabling companies to measure and reduce their real-world impact through credible data. The primary focus is corporate carbon accounting, developing and maintaining methodologies aligned with the GHG Protocol and ensuring they reflect the latest scientific developments and regulatory requirements. This means the Climate Data Scientist will directly influence how emissions are quantified, categorised and reported across scopes, sectors and business contexts. A second major focus is regulatory and disclosure readiness. As frameworks such as CSRD and ESRS evolve, Watershed's customers need audit-ready metrics that satisfy both voluntary and mandatory reporting. This role determines how those standards are encoded into the platform, which makes it central to the company's value proposition and to its clients' compliance strategies. There is also a broader sustainability science dimension, potentially spanning land sector guidance, removals accounting and sector-specific methodologies. The overarching goal is to keep the platform's scientific foundation current, defensible and actionable so that corporate decarbonisation efforts rest on numbers that hold up to scrutiny.

The most obvious challenge is the pace at which sustainability standards and scientific consensus move. The GHG Protocol, ESRS and sector-specific guidance are all evolving, and this role must decide not only what a change means scientifically but how and when it should be reflected in a live product. That demands judgement under uncertainty, because the platform's customers need stability as much as they need currency. A second challenge lies in the data itself. Corporate sustainability data is notoriously messy, incomplete and inconsistent across suppliers and business units. Building pragmatic approaches that balance scientific rigour with usability and auditability is genuinely difficult, and there will be trade-offs where no perfect answer exists. The role explicitly asks for someone comfortable navigating that ambiguity without lowering the scientific bar. The third challenge is communication. Methodology decisions must be explained convincingly to engineers, auditors, verifiers, customers and internal stakeholders who each bring different expectations. Working across a Python codebase without being a software engineer adds another layer of complexity, as does maintaining momentum across multiple product teams with competing priorities.

A typical day might begin with a methodology review or stand-up with engineers and product managers, working through a feature where a sustainability standard needs to be translated into product logic. Much of the morning could be spent in the codebase, reading implementations, writing or refining a technical specification, or checking whether a calculation behaves correctly against test cases. This is not a pure research role, so the rhythm is closer to applied science inside a product organisation. Afternoons might involve investigating a specific customer question where accounting rules, data quality and business context intersect, then documenting the reasoning so it can be reviewed and reused. There will be regular collaboration with go-to-market or customer-facing colleagues who need methodology choices explained clearly, and periodic contributions to internal standards that raise the bar for scientific quality across the team. The mix varies by project cycle. Some weeks are dominated by standards research and writing; others by close collaboration with engineering on implementation and testing. Occasional deep-dive conversations with auditors, verifiers or academic experts are likely, particularly when new guidance lands.

Watershed is a fast-growing company in climate data and analytics, so the role sits in an area with visible strategic importance. The Methodology team is described as foundational to the business, which suggests strong internal visibility for strong performers. Progression could take several forms: deepening into a principal or lead methodology role, moving toward product management where scientific expertise shapes the roadmap, or expanding into adjacent areas such as data science or sector-specific methodology ownership. Skill development is likely to be rapid and broad. The role builds expertise at the intersection of climate science, GHG accounting, regulation and software, a combination that is scarce and increasingly valuable across consulting, enterprise sustainability and climate tech. Exposure to audit and assurance processes, standards development and product engineering all compound over time. Because Watershed operates across multiple markets and sectors, there is also geographic and sectoral breadth to grow into. Leading high-visibility methodology initiatives, representing the company externally with standard-setters or auditors, and mentoring newer team members are all plausible paths as the organisation scales.

The closest working relationships will be with software engineers, data scientists and product managers, with whom the Climate Data Scientist co-designs methodology features and reviews implementations. These interactions are highly collaborative and iterative, blending scientific reasoning with product constraints. The Methodology team itself provides an internal peer group for review, standards-setting and quality assurance. Externally facing colleagues are another key stakeholder group. Go-to-market and customer-facing teams rely on this role to explain methodology choices clearly, whether to enterprise customers, auditors or verifiers. That means translating technical and scientific detail into language that supports commercial conversations and assurance processes without over-simplifying. Beyond the immediate organisation, the role likely engages with auditors, verifiers and occasionally academic or scientific experts, particularly when standards shift or novel methodological questions arise. Internal business stakeholders across product and leadership will also look to this person as a source of authority on scientific correctness, making the role a reference point for methodology decisions across Watershed.