Research Assistant, Sustainability, Climate, and Geopolitics Program -- Climate Mobility

Carnegie Endowment for International Peace

20h•$50,000 - $52,000•Hybrid

About The Position

The Sustainability, Climate, and Geopolitics Program at the Carnegie Endowment for International Peace is seeking a full-time Research Assistant based at Carnegie's Washington, DC headquarters. The selected candidate will support research on climate mobility – how people are responding to climate change by making decisions about where to live and work. The work will mostly focus on geographies outside the United States. The Research Assistant will work closely with and support the research of our leading scholars on the Program's climate mobility team.

Requirements

Demonstrated knowledge of relevant areas, including climate adaptation policy, climate and human mobility, global migration, and refugees and human displacement in the context of climate change
Experience with or interest in working with communities impacted by climate change and/or global migration, especially in Global South countries
Strong analytical and writing skills with the ability to synthesize complex technical material
A strong sense of professionalism and capacity to engage respectfully with diverse audiences
Familiarity with AI or machine-learning methods applied to social, environmental, or policy data
Experience working with large, complex, or messy datasets
Ability to meet multiple deadlines in a fast-paced work environment
Write clearly and synthesize complicated concepts
Adopt a hands-on deck approach to working in a collaborative environment

Nice To Haves

Experience in a quantitatively oriented field (e.g., economics, data science, statistics, geography, demography, computational social science, political science, or a related discipline)
Experience translating data into compelling visualizations (e.g., use of Flourish)
Experience using quantitative and computational methods for policy-relevant analysis such as causal reasoning, forecasting, scenario analysis, or simulation-based approaches
Proficiency in at least one statistical or programming environment (e.g., Python or R)