Amazon Business Analyst II Seller Experience Research 

United States, New York, New York 

183439640

We're looking for an experienced Applied Scientist with exceptional technical, analytical, and innovative capabilities to research, design, and create elegant machine learning solutions. The solutions will help our advertisers with multi-media and multi-lingual advertising offerings. You will use ideas from various domains of machine learning, including supervised and unsupervised methods, Deep Neural Networks, Natural Language Processing (NLP), and Speech to build ML models that localizes multi-media advertising contents, including audio and videos. You will also identify opportunities to leverage ML beyond localization, including, international expansion and global campaigns. Your work will directly impact our customers in the form of products and services used directly by our advertisers as well as our third-party integrators.As an Applied Scientist on this team, you will:- Perform hands-on analysis and modeling with enormous data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience.
- Work closely with software engineers on detailed requirements to productionize the ML models you build.- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
- Research new innovate machine learning approaches.

- 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

- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)