Remote Sensing Analyst

GiveDirectly

Remote Sensing Analyst leading research on economic effects of cash transfers using satellite imagery and geospatial analysis at GiveDirectly. Pioneering novel methodologies for development research in low-income settings.

Posted 6/4/2026contractRemote • New York • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

PythonRemote Sensing

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Health insurance
401(k) matching
Flexible work hours
Paid time off

ATS Keywords

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Hard Skills & Tools

geospatial analysissatellite imagery analysisGISPythonRdata processingspatial analysisdata evaluationautomated detectionquantification of changes

Soft Skills

problem-solvingproject managementattention to practical constraintsintellectual humilityclear communicationhypothesis-driven thinkingresourcefulnessdocumentation practices