Our team is passionate about Brands who sell on Amazon - we help them grow their businesses, build their story, and serve their customers. How do we do this? Data! Help us serve this valuable data to our Brands in digestible ways so they can run their businesses more effectively.
Amazon Science gives you insight into the company's approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It's the company's ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.
We are looking for an Applied Scientist who can apply the latest research, state of the art algorithms and machine learning to build highly scalable systems in the e-commerce domain. As a member of our team you will develop and evaluate machine learning models using large data-sets and cloud services to drive the growth of Brand owners on Amazon. You will have the opportunity to research and implement novel ML and statistical approaches, apply a variety of machine learning algorithms, and work on one of the world's largest data sets to influence the long term evolution of our science roadmap. You will need to understand the business requirements and translate them into complex analytical outputs. You will research, design and improve on the models that impact Amazon's customers directly. You will design tests to explain performance of the models from impact on customer and cost perspective. You should be able to present your model and findings to a various range of stakeholders.
• Designing, implementing, testing, deploying, and maintaining innovative models and data and machine learning solutions to accelerate our business.
• Creating experiments and prototype implementations of new learning algorithms and prediction techniques
• Using machine learning and statistics techniques to create scalable solutions for business problems
• Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
• Collaborating with scientists, engineers, product managers, and stakeholders to design and implement software solutions for science problems
• M.S. or PhD in Computer Science, Machine Learning, Operational Research, Statistics, or other quantitative field
• 3+ years of hands-on experience in predictive modeling, analysis, and machine learning
• 2+ years hands-on experience in Python, Scala, Java, C#, C++ or other similar languages
• Proficiency in model development, model validation and model implementation for large-scale applications
• Ability to convey mathematical results to non-science stakeholders
• Strength in clarifying and formalizing complex problems
• 4+ years of practical experience applying ML to solve complex problems in an applied environment
• Experience using an object-oriented language to write production-ready code
• Strong problem solving and algorithm design fundamentals
• Experience with defining research and development practices in an applied environment
• Excellent verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts
• Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval
• Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes.
Valid through: 11/19/2021