opengreenhousetechchange
Lead – Assessment and Impact Analytics
Bezos Earth Fund
LocationWashington, D.C., Bezos Earth Fund
Last observed2026-06-13 05:25:29.613016
Job idtechchange-bezos-earth-fund:greenhouse:4674925006
Lead – Assessment and Impact Analytics The Bezos Earth Fund is committed to rigorous analysis and assessment as it strives for the highest impact nature and decarbonization outcomes. The Earth Fund is looking for a technical lead to support grantmaking teams, and provide analytical and decision support across its grantmaking portfolio. Key Responsibilities: The Earth Fund is looking for a technical lead to provide quantitative, technoeconomic and analytical assessments and decision support for its grantmaking portfolio, inform the Fund’s strategic direction, and support the effective allocation of resources to address nature and climate goals. The position requires an adept and experienced researcher with strong analytical skills and a background in decision support around climate and nature strategies. The Lead – Assessment and Impact Analytics will collaborate with grant leads across a range of portfolios, bringing an agile and supportive approach, to enhance the impact of the Fund’s work. The position will report to the Chief of Science, Data, and Systems Change and work closely with the Monitoring, Evaluation and Learning Lead. The Lead – Assessment and Impact Analytics will have the following responsibilities: Collaborate with grant leads to estimate the impacts of their grant portfolios and strategies, focusing on, but not limited to greenhouse gas emissions reductions and nature outcomes. Develop an approach and lead technoeconomic assessments of climate and nature interventions, as relevant, evaluating technology readiness, performance potential, scalability, and cost-effectiveness. Support decision making by integrating engineering, economic, and environmental analyses across multiple sectors (e.g. energy, industry, land use). Provide technology-to-market insights, identifying barriers, enablers, and inflection points for innovation scale-up. Evaluate risks, uncertainties, and opportunity spaces associated with emerging technologies and interventions. Assess and develop tools, methods, and data (e.g. standardized scenarios) that can be applied across the Earth Fund’s portfolio to ensure consistency in decision making. Provide cross-cutting support to incorporate rigorous analytical methods into decision making (e.g. scenario analysis, energy modeling, economic modeling, land use modeling). Gather and synthesize large external datasets into clear, compelling data products to support decision-making needs. Provide or commission custom analytical outputs to support staff on topics of strategic importance. Stay informed of the latest knowledge, analysis, and research related to impact estimation, accounting, and decarbonization and land use outcomes. Build and maintain an external network to remain up to date on advances in energy policy and climate change and nature analytics and modeling. Collaborate with grant leads and the Monitoring, Evaluation and Learning Lead to assess and communicate the impacts of the Earth Fund’s proposed and existing grants internally and externally. Serve as an analytical and decision support resource across the Earth Fund team. Liaise with the Earth Fund communications team, as necessary, to inform storytelling. Perform other duties as assigned. Education and experience: Master’s Degree or PhD with a strong emphasis on quantitative methods for decision making. At least 10 years of full-time work experience on climate- and/or nature-related issues. Demonstrated ability to apply rigorous analysis to inform strategic decisions in real world settings. Demonstrated experience in GHG impact assessment, technology evaluation, technoeconomic assessment, and/or decision support related to climate or nature. Skills and abilities: Proven track record of using quantitative methods to inform strategic decisions around greenhouse gas outcomes and nature protection. Familiarity with relevant forecasting models around climate and nature (e.g. emissions scenarios) and greenhouse gas accounting methods for a
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