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Limitless High-tech career opportunities - Expoint

Amazon Applied Scientist Sponsored Products 
United States, Washington, Seattle 
13678085

Today
DESCRIPTION

As an Applied Scientist, you will partner with other talented scientists and engineers to design, train, test, and deploy machine learning models. You will be responsible for translating business and engineering requirements into deliverables, and performing detailed experiment analysis to determine how shoppers and advertisers are responding to your changes.Key job responsibilities
As an Applied Scientist on the Search Supply & Experiences team you will:- Perform hands-on analysis and modeling of enormous datasets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.
- Drive end-to-end machine learning projects that have a high degree of ambiguity, scale, and complexity.
- Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
- Design and run experiments, gather data, and perform statistical analysis.
- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
- Stay up to date on the latest advances in machine learning.

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 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 in professional software development
- Have publications at top-tier peer-reviewed conferences or journals
- Experience implementing algorithms using both toolkits and self-developed code