Amazon Senior Applied Scientist Fulfillment Planning 

United States, Washington, Bellevue 

350020790

Key job responsibilities
As a Senior Applied Scientist within FPX Science team, you will propose and deploy solutions that will likely draw from a range of scientific areas such as Optimization, machine learning, advanced statistical modeling, and graph models. You will have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry, with some of the best product managers, research scientists, statisticians, and software engineers to integrate scientific work into production systems. You will bring deep technical expertise in the area of Optimization, and will play an integral part in building Amazon's Fulfillment Optimization systems. Other responsibilities include:* Design, development and evaluation of highly innovative Math models for solving complex business problems.
* Research and apply the latest Optimization techniques and best practices from both academia and industry.
* Think about customers and how to improve the customer delivery experience.
* Use and analytical techniques to create scalable solutions for business problems.
* Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale.
* Technically lead and mentor other scientists in team.
* Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
A day in the life

- 5+ years of applied research experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- 5+ years of industry or academic research experience
- Ph.D. in Operations Research, Computer Science, Industrial Engineering, Statistics, Applied Mathematics, or a related field
- 5+ years of hands-on experience in building optimization models in business environment
- Proven track in leading and mentoring scientists with demonstrated ability to serve as a technical lead
- Strong fundamentals in problem solving, algorithm design and complexity analysis

- Experience in building machine learning models for business application
- Deep technical knowledge of optimization models
- Prior experience modeling supply chain related problems
- Experience of applying hybrid techniques in the space of ML and Operations Research is a big plus
- Experience with high-impact decisions (>$1B)