Data Scientist Amazon
Seattle, WA

Job Description

We are growing and taking on more to make the world safe for ecommerce. Amazon.com's TRMS team is a centralized technology team that works to make Amazon the safest and most trusted marketplace online and offline for our Buyers and Sellers by defending Amazon accounts from malicious actors. These systems, invisible to the customer, work seamlessly across the billions of transactions occurring simultaneously around the world. Come build with us! Because of Amazon's huge scale, this a great opportunity to add hundreds of millions to the bottom line and protect Customers everywhere.

We are seeking an innovative, results-oriented, customer-centric data scientist to drive expansion of innovative ML solutions globally in the Account Integrity space. As a Data Scientist, you will be responsible for modeling complex problems, 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 cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. The candidate 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.

Responsibilities:

* Use predictive analytics and machine learning techniques to solve complex problems and drive business decisions.
* Employ the appropriate algorithms to discover patterns of risks, abuse and help reduce bad actor activity
* Design experiments, test hypotheses, and build actionable models to optimize TRMS operations
* Solve analytical problems, and effectively communicate methodologies and results
* Build predict models to forecast risks for product launches and operations
* Draw inferences and conclusions, and create dashboards and visualizations of processed data, identify trends, anomalies
* Work closely with internal stakeholders such as business teams, engineering teams, and partner teams and align them with respect to your focus area