- Beijing, China
Amazon Logistics is building geospatial infrastructure to power the Last Mile delivery network that will deliver packages to hundreds of millions of customers around the world. The Amazon Maps Data team builds systems that model the real world to enable routing for drivers. The GIS team works cross-functionally to seamlessly curate and enhance last mile delivery network and geospatial data quality.
We are looking for smart, passionate people to join our GIS team. You will make help Amazon Logistics drivers be successful and efficient through process innovations and improvements. You will help increase their productivity and quality through GIS models and, ultimately, ensure we provide our drivers with a hassle-free delivery route that they love. This role is inherently cross-functional- you will work closely with engineering, operations, data science, business intelligence and other teams on spatial challenges and drive them to resolution through high quality maps, spatial analysis and data visualizations.
• Work on large spatial and non-spatial dataset including rasters
• Work on proprietary and open source GIS platforms like QGIS, GeoDjango and Python along with managing open source spatial databases like PostGRES
• Optimize existing processes through customized solutions and robust models
• Create and managing large spatial databases for GIS modeling;
• Work on open source (Web, desktop, database) and on proprietary GIS software, develop models for process automation
• Extract valuable insights from large, complex spatial and non-spatial data sets using GIS tools and techniques
• Graduate or post graduate or specialization in GIS from esteemed university
• 4+ years of experience in working with GIS and satellite images with expertise in handling various vector and raster datasets
• Knowledge about projections, coordinate systems, georeferencing, map publishing using server architecture and modelling
• Strong analytical and problem solving skills
• Strong written and oral communication skills
• Experience in spatial data quality assessment and insight generation
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