Fraud & AML Analytics Strategist

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:

If you thrive on curiosity, creativity, and staying a step ahead of fraudsters, this role is for you. You’ll bring together a deep understanding of fraud and AML patterns to craft new rules, the curiosity to test emerging data signals, and the discipline to design workflows that both protect customers and keep their experience seamlessly.

You’ll thrive here if you enjoy asking “what if?” — what if attackers shift their tactics, what if a new payment method introduces risk, what if a simpler workflow could reduce friction without losing protection. Your work will directly shape how we protect our customers across money movement, account origination, and card transactions, and you’ll have the freedom to experiment, iterate, and turn insights into impactful strategies.

Key Responsibilities:

• Proactively design, test, implement, and optimize rules for fraud and AML detection across origination, money movement, card, and suspicious activity monitoring.
• Manage rule libraries, ensuring governance, monitoring, and compliance alignment.
• Run experiments and pilot new approaches to detect emerging fraud and AML typologies.
• Collaborate with Data Science to translate fraud patterns and AML scenarios into model features.
• Partner with Fraud & AML Operations for case feedback and validation of coverage.
• Define and manage fraud/AML workflows (queues, alerts, escalation paths).
• Evaluate external fraud and AML data providers for enrichment opportunities.
• Provide fraud and AML insights, typology analysis, and strategy recommendations to leadership.
• Partner with Product, Engineering, and Commercial teams to embed proactive fraud and AML strategies into the platform and client dashboards.