Fraud Strategy Manager

DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us! 

Position Overview:

As a Fraud Strategy Manager, (FSM), you are responsible for leveraging our state-of-art fraud detection SaaS products to solve our key clients' fraud and risk problems. You provide technical solutions and consultative services of our state-of-art fraud detection SaaS products​ to a portfolio of Fortune 500 customers in FinTech, Banking, E-commerce industries. From managing detection system performance to debugging product issues, you are an expert who can provide technical guidance and share best practices with customers on using our Machine Learning models, Rules Engine, and Device Intelligence Signals to detect fraud and risks. You work cross-functionally with Engineering and Product teams to implement new ideas to our analytics system.

This is a remote-based position and can be located in the U.S. or Canada, preferably in the Eastern Time Zone.

Key Responsibilities:

• Understand client use cases and define plans to achieve success criteria
• Lead technical discussion for fraud deep dives that prepare for detection modules’ success   
• Guide and work with our ML modeling team to monitor and enhance the detection quality
• Lead the implementation of detection logic and rules to enhance detection quality
• Attend meetups, events, and conferences as a technical ambassador