Amazon Applied Scientist - Operations Research/Optimization 

United States, Washington, Seattle 

816600042

In this role, you will have an opportunity to both develop advanced scientific solutions, and drive critical customer and business impacts. You will play a key role to drive end-to-end solutions from understanding our business requirements, exploring a large amount of historical data, building, managing and improving optimization, simulation and HOTW decision models, building prototypes and products, and exploring conceptually new solutions, to working with partner teams for prod deployment that will be used primarily for Promotion Optimization and Scenario Planning Capabilities for in-period promotion, and long-term financial planning.You will collaborate closely with scientists, engineering peers as well as business stakeholders. You will be at the heart of a growing and exciting focus area for Amazon Devices and Services.You are an individual with outstanding analytical abilities, excellent communication skills, and are comfortable working with cross-functional teams and systems. You will be responsible for researching, prototyping, experimenting, analyzing prescriptive optimization models and developing smart automation solutions.
Key job responsibilities
- Develop and maintain optimization frameworks, libraries, and tools to enable scalable and efficient optimization and automation capabilities
- Analyze optimization results, identify bottlenecks, and continuously improve the performance and accuracy of optimization models
- Stay up-to-date on the latest academic research and industry best practices in optimization techniques and tools, and identify opportunities to apply new approaches
A day in the life

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience in optimization: linear, non-linear, mixed-integer, large-scale, network, robust, stochastic and/or dynamic