We’re working on the future. If you are seeking an iterative fast-paced environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide visible benefit to customers, this is your opportunity.
Come work on the Amazon Prime Air Team!
We are looking for an Applied Scientist II with expertise with geospatial data analysis and GIS technologies.
As an Applied Scientist II, you will contribute to the Prime Air project by working with Systems and Software Engineers and Scientists, participate in the Science community at Amazon, and collaborate with academic researchers in the broader academic community. Within Prime Air our Science community values teamwork and supports continued learning. Furthermore, our builder culture means that Scientists and Software Development Engineers work closely together to invent and construct solutions that must work at scale.
Export Control License
This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon’s ability to apply for and obtain an export control license on your behalf.
· Prototype and implement new algorithms and concepts for geospatial data modeling and analysis.
· Perform studies to determine the impacts of new design concepts on overall system performance.
· Collaborate with product managers and engineering teams to design and implement software solutions for challenges.
· Drive collaborative research and creative problem solving.
· Constructively critique peer research and mentor junior scientists and engineers.
· Contribute to progress of the Amazon and broader research communities by producing publications.
· Ph.D. in Geospatial Computer Science, Aerospace Engineering, or a similar quantitative research field.
· Experience programming in Java, C++, Python or similar language.
· Experience or academic background with geospatial data and GIS software.
· Ability to quickly understanding short-comings with various technical approaches and suggest mitigations.
· Demonstrated abilities in distilling problem definitions, models, and constraints from complex business problems and requirements.
· Significant peer-reviewed scientific contributions in premier journals and conferences.
· Practical experience solving complex problems in an applied environment.
· Professional software development experience.
· Strong CS fundamentals in data structures, problem solving, algorithm design, and runtime complexity analysis.
· Experience applying machine learning algorithms and data science best practices.
· Superior verbal and written communication and presentation skills, ability to convey complex concepts and considerations to non-experts.
· The leadership capacity to influence the technical direction of a new product while ensuring a team-oriented approach to delivery in an agile software development environment.