Remote Sensing Analyst

This is a fully remote position, open to applicants in New York.

📋 Description

• Lead the design of geospatial analyses: Collaborate with the GiveDirectly research team to convert research hypotheses regarding market effects into testable geospatial indicators (e.g., agricultural intensification, road quality, population clustering, infrastructure development).

• Identify and assess imagery options: Discover, evaluate, and acquire satellite imagery or telecom data from diverse sources for study areas; assess data quality, temporal resolution, and relevance for hypothesis testing.

• Perform exploratory analysis and interpret results: Conduct spatial analyses on smaller samples of pilot data to identify changes in agricultural composition, cultivation intensity, infrastructure, and economic activity spatial patterns.

• Create repeatable analysis scripts: Develop reproducible, well-documented code (using Python/R/GIS tools) for the automated identification and quantification of landscape and infrastructure changes over time.

• Document and communicate findings: Produce clear technical documentation, methodology notes, and summaries of findings that are accessible to both technical and non-technical audiences.

⛳️ Requirements

• Strong alignment with GiveDirectly Values and active demonstration of our core competencies: intellectual humility, problem-solving, project management, follow-through, and attention to practical constraints.

• Advanced expertise in geospatial and remote sensing: Proven experience in satellite imagery analysis, GIS platforms (ArcGIS, QGIS), and the interpretation of geospatial data.

• Proficient programming skills: Competence in Python, R, or similar programming languages for processing and analyzing geospatial data; ability to produce clean, well-documented, reproducible code.

• Hypothesis-driven mindset: Capability to convert economic and social research questions into technical geospatial proxies; experience in supporting economics projects is advantageous.

• Resourcefulness in data handling: Experience in sourcing, evaluating, and utilizing open-source or low-cost data sources; ability to troubleshoot issues related to data quality and availability.

• Effective communication skills: Proficiency in conveying technical findings to non-specialists; strong documentation practices; ability to bridge the gap between research and implementation teams.

🏝️ Benefits

• Health insurance

• 401(k) matching

• Flexible work hours

• Paid time off