Job Description

• 3+ years of investigating the feasibility of applying scientific principles and concepts to business problems and products experience
• PhD, or Master's degree and 5+ years of quantitative field research experience
• Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.
• Experience communicating qualitative research methods and findings to non-qualitative researchers


Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon continues to grow and evolve as a world-class e-commerce platform. The AOP team is an integral part of this and strives to provide Analytical and Science Capabilities for ROW (Rest of the World) Operations. We are looking for a Senior Research Scientist interested in solving challenging Capacity Optimization problems across various miles of Amazon Operations. These problems have significant impact on our reliability, speed, cost and productivity.

As a Senior Research Scientist in AOP, you will be focused on leading the design and development of innovative approaches and science solutions to solve multi-geo optimization problems. You will also be working closely with Scientists in global teams to converge these solutions with global roadmaps.

You will suggest best practices and take on a lead role with junior scientists and BIEs in the team. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail and outstanding ability in balancing technical leadership with strong business judgment to make the right decisions about model and method choices.



The Research Scientist will develop & support our capacity planning products using Simulations, Integer Programming, Linear Programming, Heuristic search and Machine Learning. This Scientist, will work closely with our program partners to define business requirements, build data pipeline, write optimization code, identify the right ML models, deep dive on solution quality and drive adoption with operations.



Key job responsibilities

1. Provide technical expertise to identify science models and strategies that will allow AOP to deliver massive cost savings for ROW countries.

2. Being able to implement Operations Research and Machine Learning models into production environments

3. Implement best practices and mechanisms to improve the overall science implementation framework of the team

4. Work closely with Product Managers, Operations Managers and Ops Leaders to improve explainability and bridging of solutions

5. Partner with other global science teams to align and merge with central strategy



• Experience converting research studies into tangible real-world changes
• Experience with discrete and continuous optimization methodologies and algorithms
• Experience in putting large scale models into production will be a plus point