Lead geospatial analysis design: Work with the GiveDirectly research team to translate research hypotheses about market effects into testable geospatial proxies (e.g., agricultural intensification, road quality, population clustering, infrastructure development).
Source and evaluate imagery options: Identify, assess, and procure satellite imagery or telecom data from various sources for study areas; evaluate data quality, temporal resolution, and suitability for hypothesis testing.
Conduct exploratory analysis, and interpret findings: Execute spatial analysis on smaller samples of pilot data to detect changes in agricultural composition, cultivation intensity, infrastructure, and spatial patterns of economic activity.
Develop repeatable analysis scripts: Build reproducible, well-documented code (Python/R/GIS tools) for automated detection and quantification of landscape and infrastructure changes over time.
Document and communicate: Create clear technical documentation, methodology notes, and findings summaries suitable for both technical and non-technical audiences.

Exceptional alignment with GiveDirectly Values and active demonstration of our core competencies: intellectual humility, problem-solving, project management, follow-through, and attention to practical constraints.
Strong geospatial and remote sensing expertise: Demonstrated experience with satellite imagery analysis, GIS platforms (ArcGIS, QGIS), and geospatial data interpretation.
Technical programming skills: Proficiency in Python, R, or similar languages for geospatial data processing and analysis; ability to write clean, documented, reproducible code.
Hypothesis-driven thinking: Ability to translate economic and social research questions into technical geospatial proxies; experience working with or supporting economics projects a plus.
Resourcefulness with data: Experience sourcing, evaluating, and working with open-source or cost-effective data sources; comfort troubleshooting data quality and availability constraints.
Clear communication: Ability to explain technical findings to non-specialists; strong documentation practices; comfort translating between research and implementation teams.

Remote Sensing Analyst

Key skills