The External System Integration (ESI) team enables Amazon Business to be the preferred procurement solution for enterprises through seamless integrations with external procurement systems. ESI team's charter focuses on allowing businesses of all sizes to integrate Amazon Business with their existing infrastructure (procurement, website, mobile applications, automated systems, etc).

As the ESI team's Senior Applied Scientist, you'll be at the forefront of applying AI to solve real-world business problems that directly impact Amazon's fastest-growing segment. In this role you'll have the unique opportunity to build AI systems that serve millions of business customers. This role combines the intellectual challenge of novel AI research with immediate business impact. This is an exciting opportunity to establish AI leadership in B2B procurement working on problems at scale that do not exist anywhere else in the industry.

Senior Applied Scientists at Amazon are trusted technical leaders who tackles intrinsically complex scientific problems by leveraging experience and expertise with machine learning algorithms. They innovate and set standards for scientific excellence, making decisions that affect the way the algorithms are built and integrated. They scrutinize and review experimental design, modelling choices and the implementation strategy to ensure sustainability and generalizability. They align teams towards coherent strategies and guide their peers towards adopting latest scientific trends. They force multiply by decomposing a hard problem into pieces and get them executed through collaboration. They solicit differing views across the organization and are willing to change their mind as they learn more. They are capable of working with a diverse set of stakeholders and influencing leaders by converting ideas into business impact.


Key job responsibilities
- Define research directions by adopting state-of-the-art technology and innovating new solutions
- Perform experiments to convert ideas into actual business impact
- Develop long-term strategies and jointly design and deliver on goals
- Participate in hiring, mentorship and development of the Science community
- Acquire domain expertise and in-depth understanding of related engineering systems
- Contribute through patenting and publishing

Basic Qualifications

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience

Preferred Qualifications

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.

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