Senior Applied Scientist, Amazon

• PhD degree in Computer Science or related field
• Several years experience building machine learning models for business applications using Python, Java, C++ or related language
• Documented expertise in machine learning/artificial intelligence: data processing, neural networks, deep learning, estimators, regression, information theory, optimization, statistical analysis, signal processing, graph mining, causality analysis
• Experience with patents or scientific publications at peer-reviewed conferences or journals and generally excellent writing and communication skills

Desirable

• As a Sr. Applied Scientist of the Engine AICE team, you have the important role of mapping business challenges to high-impact solutions in areas where the business problem or opportunity may not yet be defined
• You turn theoretically sound methods into practically applicable models designed for processing massive volumes of data in large-scale environments
• You define business relevant solutions implemented as end-to-end machine learning functions and data processing pipelines that integrate with our partners production systems
• In a fast-paced innovation environment, you advise and work closely with our Applied Scientists, Machine Learning Engineers, Software Development Engineers, and partner teams to design machine learning models and experiments at scale
• You are recognized for your expertise in all aspects of the practical machine learning development cycle, encompassing sound use of data pre-processing techniques, analysis, modelling, and validation methods
• You take lead of the scientific and technical work in cross-team collaborations
• We work back to back to address the technical challenges of automation across a variety of products, software, and systems
• Our scientists and machine learning engineers work in synergy to solve hard problems and enrich each other's skills
• Together, we are a diverse team of specialists that bring the potential of practical machine learning to the max with impact on millions of Amazon customers