June 14, 2022

2022 Fall Research Science Intern – Aerospace, Deep Learning, Industrial Engineering, Machine Learning, Operations Research, Quantum, Robotics (EE/Mech Eng.)

  1. https://www.amazon.jobs/en/jobs/2052468/
  2. https://www.amazon.jobs/en/jobs/2050723/

Job summary
As a research science intern, you will be working closely with fellow research scientists and research interns. You will use your experience in modeling, statistics, and simulation to design models of new processes, simulate their performance, and evaluate their benefits and impacts to cost, reliability, and speed. You will have access to rich datasets to develop mathematical models, create high visibility analytics, and have influence to the direction of the company.

This internship requires superior analytical thinking, and ability to apply technical and statistical knowledge to identify opportunities for real world applications. You should be able to mine and analyze large data, and be able to use necessary programming and statistical analysis software/tools to do so.

You should thrive in ambiguous environments that require to find solutions to problems that have not been solved before. You leverage your exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience. Your strong communication skills enable you to work effectively with both business and technical partners.

Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.

Please visit https://www.amazon.science for more information.

·Enrolled in a PhD degree or equivalent in Engineering, Technology, Science, Operations Research, Robotics, Mathematics or a related quantitative field
· Relevant experience in at least one of the related science disciplines (optimization – LP, MIP, Statistics, Machine Learning, Process Control, Combinatorial Optimization)
· Experience with SQL and Statistical/mathematical programming software packages (e.g., R, SPSS, CPLEX, LONDO or Xpress, etc.).
· Experience in problem solving and data analytics.

· Fluency in at least one programming or scripting language (e.g., Python, Java, C, C++)
· Demonstrated deep expertise in at least one of the related science disciplines (optimization – LP, MIP, Statistics, Machine Learning, Process Control, Combinatorial Optimization)
· Excellent written and verbal communication skills.
· Experience working with data mining on large datasets (“big data”).