Fraud Detection Supervisor supervises fraud detection associates in their effort to detect possible customer fraud. Leads cross-functional initiatives to proactively detect and prevent fraud from occurring. Being a Fraud Detection Supervisor researches, documents, and implements best practices in the industry with regard to fraud detection. Leads the most challenging and complex fraud investigations. Additionally, Fraud Detection Supervisor requires a bachelor's degree. Typically reports to a manager or head of a unit/department. The Fraud Detection Supervisor supervises a group of primarily para-professional level staffs. May also be a level above a supervisor within high volume administrative/ production environments. Makes day-to-day decisions within or for a group/small department. Has some authority for personnel actions. Thorough knowledge of department processes. To be a Fraud Detection Supervisor typically requires 3-5 years experience in the related area as an individual contributor. (Copyright 2024 Salary.com)
DataVisor is a next generation security company that utilizes industry leading unsupervised machine learning to detect fraudulent activity for financial transactions, mobile user acquisition, social networks, commerce and money laundering. Our solution is used by some of the largest internet properties in the world, including Pinterest, Synchrony Financial, AirAsia and PingAn, to protect them from the ever-increasing risk of fraud. Our award-winning software is powered by a team of world-class experts in big data, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results driven. Come join us!
The Data Science/Modeling team holds the secret sauce of DataVisor. We run our advanced core unsupervised analytics engine and machine learning models on hundreds of billions of events from hundreds of millions of users. We are a mix of big data software engineers and inquisitive data scientists. We love finding beautiful patterns in data to catch and prevent malicious attacks against normal good users. We’re also not afraid to get our hands dirty; we get deep satisfaction coming up with and implementing new ideas for improvements to our detection engine. If you have a knack for mining fraud patterns while wrangling big data, are excited by building world class anti-fraud models, and want to work on a team that impacts the company’s bottom line, we’d love to talk to you.