Do you want to join an innovative team of scientists who use machine learning to help Amazon
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Key job responsibilities
- Use statistical and machine learning techniques to create the next generation of the tools that empower Amazon Selling Partners to succeed.
- Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions.
- Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features.
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
- Research and implement novel machine learning and statistical approaches.
- Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment.
About The Team
Selling Partner Experience Science is a growing team of scientists, engineers and product leaders engaged in the research and development of the next generation of ML-driven technology to empower Amazon Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. Focused on collaboration, innovation and strategic impact, we work closely with other science and technology teams, product and operations organizations, and with senior leadership, to transform the Selling Partner experience.
We are open to hiring candidates to work out of one of the following locations:
Herndon, VA, USA | Seattle, WA, USA
Basic Qualifications
- 4+ years of applied research experience
- 3+ years of building machine learning models for business application experience
- PhD, or Master degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
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.