欢迎投递 zhihan@ebay.com, 广告和搜索也可
At eBay, you will be part of a purpose driven community dedicated to creating a bold and versatile work environment. In eBay Payments, you will be an integral member of a growing organization that inspires passion, courage and inventiveness - creating the future of global commerce and making an important, positive impact on millions of eBay sellers and shoppers around the world. If you are looking for a special place to take your Payments career to the next level, we want to talk with you!
Risk Management is at the core of Payments done well – and we are hiring curious, driven, and courageous experts to transform our business unit to enable eBay's next generation Payments strategy. Our focus is to ensure the integrity of our marketplace for buyers and sellers who transact with us every single day. The scope of our charter includes Risk Management Strategy, Policy, Decision Management, and Policy Operations.
We are looking for a highly talented and self-motivated applied researcher to join our Decision Science team. Decision Science contains both applied researchers and software engineers responsible for creating and implementing state of the art machine learning algorithms for fraud detection and risk assessment in support of Risk Management. .
The primary responsibility of this role is to build and deploy AI algorithms inside of a high throughput, low latency and customer facing environment. The applied researcher will support the risk department, leveraging big data technologies to aggregate and structure data, perform statistical analysis, and build algorithmic solutions to reduce fraud, monitor our buyers and sellers, and intermediate payments to improve the overall eBay experience. As a member of the decision science team, you will research and develop new methodologies and techniques to improve the overall effectiveness of risk management. Mine and analyze massive amounts of unique internal and external data to gain deep business knowledge and insight on customer activity and usage behaviors and their relationships with fraud, credit risks, and other types of behaviors. The ideal candidate is a blend of science and engineering skills with capabilities stretching from problem statement to algorithm deployment.
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