Sr. Data Scientist Amazon
Seattle, WA

Job Description

North America Consumer is one of Amazon's largest businesses, including North America retail and third party sellers, as well as an array of innovative new programs including Alexa Shopping and Amazon Business. The NA Consumer Finance organization is looking for a smart, motivated, and driven Sr. Data Scientist to build out a new source of analytical capability for the team. In this critical role, the successful candidate will influence decisions by making improvements to existing financial models as well as implementing state-of-the-art solutions to never before solved problems. In doing so you will provide perspective on the most important business issues that affect a wide diversity of customers and products.

As a Sr. Data Scientist you will be responsible for modeling complex business challenges, discovering insights and identifying opportunities through the use of statistical, machine learning, algorithmic, data mining and visualization techniques. You will need to collaborate effectively with internal stakeholders and finance team members, and should be able to apply a breadth of tools, data sources and analytical techniques to answer a wide range of high-impact business questions and present the insights in concise and effective manner. Additionally, the candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences.

What you will do:

* Translate ambiguous business questions and concerns into specific quantitative questions that can be answered with available data using sound methodologies.
* Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving business performance.
* Analyze historical data to identify trends and build causal elasticity estimates.
* Improve upon existing methodologies and financial models by developing new data sources, testing model enhancements, and fine-tuning model parameters.
* Partner with central economics, machine learning, finance and other analytics teams to ensure the most efficient and effective allocation of resources to tackle our team's agenda.
* Build decision-making models and propose solution for the business problem you defined.
* Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.