Amazon Web Services (AWS) is the leading provider of cloud computing services in the world, offering a broad range of highly reliable, scalable, low-cost cloud services across over 190 countries. AWS infrastructure powers hundreds of thousands of enterprise, government and start-up businesses, including industry leaders such as Amazon.com, Netflix, Expedia, Airbnb, and many more, and renowned organizations such as NASA, the Centers for Disease Control and Prevention (CDC) and Coursera. Though already very successful AWS continues to be a high-growth, fast-moving division within Amazon with a start-up mentality where new and diverse challenges arise every day.
The AWS Central Economics team includes renowned experts in the area of forecasting, causal inference and machine learning and applies economic theory and econometric analysis to build models, systems and tools that inform critical decisions for the AWS business. Such decisions include service valuation and pricing, infrastructure and hardware investments, sales and marketing investments, etc, and can each impact the allocation of hundreds of million $.
As a Sr. Data Scientist on this team, you will be a business leader, helping set the direction for the team, setting requirements for the data infrastructure, deciding on the best methodology to address a particular problem, generating models and pulling together insights to inform specific business questions.
The ideal candidate will be an expert in the areas of data science, machine learning and statistics, with extensive hands-on experience and the ability to balance technical and business considerations to make the right decisions about technology, models and methodologies. They will be a self-starter, comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment, and an ability to work effectively in cross-functional teams. They will have excellent oral and written communication skills including the ability to communicate effectively with both technical and non-technical stakeholders at all levels, and a proven ability to meet tight deadlines, multi-task, and prioritize work.
Key responsibilities include:
* Working with business and science stakeholders to understand requirements and effectively prioritizing * Collaborating with colleagues from multidisciplinary science, engineering and business backgrounds * Applying Statistical, Data Science, Machine Learning or other innovative methods to specific business problems and data * Working with engineers to develop efficient data querying and modeling infrastructure and is putting methods/algorithms into production * Communicating proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions
Amazon is a company operating a marketplace for consumers, sellers, and content creators.