At Amazon, we strive every day to be Earth’s most customer centric company. Selling Partner Experience Science (SPeXSci) delivers on this by building AI-enhanced experiences, optimization, and automation that help third-party sellers build more successful businesses.
This includes recommendations that drive growth and AI-enhanced assistance for troubleshooting issues. There are many challenges that we confront caused by the volume, diversity, and complexity of our selling partner's needs and we are always striving to do better.
Do you want to join an innovative team who creatively applies techniques ranging from statistics and traditional machine learning to deep learning and natural language processing?
A team that drives our flywheel of improvement by hunting down opportunities to do better that are buried in tens of millions of solved cases?
Are you interested in helping us redefine what world class support can be in an age of automation and AI, while prizing human empathy and ingenuity?
The SPeXSci Team is looking for an Applied Scientist to build statistical and machine learning solutions that help us understand and solve our most challenging problems.
We need to better understand our Sellers and the problems they face, to design permanent fixes to recurring problems, to anticipate problems so that we are prepared to deal with them, to measure our success at delighting our customers, and to identify opportunities to grow and improve.
In this role, you will have ownership of the end-to-end development of solutions to complex problems and you will play an integral role in strategic decision-making.
You will also work closely with engineers, operations teams, product owners to build ML pipelines, platforms and solutions that solve problems of defect detection, automation, and workforce optimization.
We are open to hiring candidates to work out of one of the following locations :
Seattle, WA, USA
BASIC QUALIFICATIONS
- 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 in patents or publications at top-tier peer-reviewed conferences or journals
- 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
PREFERRED QUALIFICATIONS
- Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
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