Fraud Analytics Manager
At OPSkins, our customers’ security is a top priority. We are looking for a data driven and highly analytical Fraud Analytics Manager to lead our payment processing fraud prevention team. As a Fraud Analytics Manager, you will mitigate payment processing fraud using pattern recognition and identity management techniques. In addition, you will instruct, review and mentor a team of Fraud Analysts on a daily basis.
- Protect the company and our customers by monitoring credit card deposits, debit card deposits and other high volume ecommerce payment methods for suspicious activity.
- Build analytical models to identify anomalous credit card purchase activity using data analysis tools from information extracted from a MYSQL database
- Improve upon the Company's well designed existing fraud analysis techniques with state of the art approaches you have either developed or have used in a high volume ecommerce environment
- Develop and lead a team of 5-10 Fraud Analysts; direct the daily tasks of the team and report team performance on a daily basis
- Design and roll out new fraud prevention tools
- Work with the software development team to create new solutions to fight fraud
- Recruit new Fraud Analysts. Be curious and self-aware
- At least 5 years of experience as a data driven Fraud Analytics Manager in a high volume ecommerce environment. With a focus on prevention.
- At least 5 years of experience managing a team of Fraud Analysts
- Strong data analytics background - ability to run sophisticated data set queries in order to identify sources of fraud.
- Substantial daily experience with forensic and statistical analysis tools used to identify suspected fraudulent activity.
- Experience in a fraud prevention management role for a high volume ecommerce company or high volume online marketplace (ecommerce experience with digital assets desirable)
- Experience with Sift Science, Kount or similar fraud prevention systems required
- Experience using analytical monitoring tools such as Domo, Periscope (or similar data warehousing systems)
- Demonstrated experience with root cause problem solving techniques
- Ability to integrate analytical thinking, past experiences and methodologies, market analysis and company goals to drive client solutions
- Bachelor’s degree in economics, engineering, statistics, math, computer science is required (Master's degree is desirable
- Fraud analysis and prevention certifications are desirable