Job Description

The Remote Sensing/Lidar Data Analyst at the Yale Center for Geospatial Solutions will help to process a multitude of remotely sensed data sets (e.g., high spatial/temporal multispectral imagery, airborne/UAVborne lidar) over different spatiotemporal scales for diverse applications. Experience with geospatial data processing in python and figure creation in python/arcgis/qgis is mandatory. The Analyst could be provided with training in advanced point cloud processing pipelines (e.g., segmentation, deep learning) and would employ those pipelines on lidar derived point clouds. Experience with processing (e.g., pdal, open3d, lidR, etc.) and/or rendering (e.g., potree, unreal, unity, etc.) large 3D datasets is a plus. Depending on the project, the Analyst could be listed as a coauthor on a peer-reviewed publication stemming from their work.

Key Responsibilities

·      Programmatically access and process large datasets

·      Compile existing data from different sources/providers

·      Derive statistics from gridded data at varying scales

·      Python data analysis as needed

·      Create charts/plots to better understand data

·      Generate slide decks highlighting workflows and outputs

·      Update supervisor on progress and outputs

Personal attributes

·      Curious and willing to learn new tools or processes as needed

·      Reliable and proactive, with a strong sense of ownership

·      Organized and detail-oriented

·      Confident making decisions independently

·      Collaborative and responsive when working with a team