About this role
Role Overview
Design, document, and refine advanced financial-crime detection frameworks and scenario libraries that train and evaluate next-generation AI systems. This role converts hands-on operational expertise in AML, fraud, and scam detection into realistic scenarios, benchmarks, and guidance used to improve AI model detection and risk scoring.
Key Responsibilities- Design and document a comprehensive library of fraud, scam, money laundering, and abuse scenarios for financial platforms.
- Identify and define social-engineering red flags and typologies, including phishing, synthetic identity fraud, and marketplace abuse.
- Create escalation grading scales and frameworks to assess severity and risk of various financial crime events.
- Develop benchmark criteria and detection frameworks to evaluate AI model capability to recognize realistic fraud patterns and suspicious activity.
- Review and enhance written guidance, operational workflows, and best practices for financial crime and AML compliance operations.
- Provide detailed, domain-accurate feedback on project deliverables to ensure practical relevance.
- Collaborate with cross-functional teams to translate subject-matter insights into actionable detection and prevention strategies.
- Apply your domain expertise to help train next-generation AI systems, no prior AI experience required.
- Required skills and domain areas: AML, fraud, marketplace abuse, phishing, synthetic identity, money laundering, scams.
- 5+ years of recent, hands-on experience in fraud investigations, AML compliance, payments risk management, or related financial crime roles.
- Practical experience detecting and analyzing scams, phishing, money laundering, synthetic identity fraud, or marketplace abuse in environments such as fintech, banking, crypto, or digital payments.
- High credibility in financial crime prevention, supported by a record of operational excellence and thought leadership.
- Advanced degree or professional certification such as CAMS, CFE, CFCS, or equivalent operational credentials in financial crime, AML, CTF, or compliance.
- Exceptional written and verbal communication skills, able to explain complex scenarios and frameworks to technical and non-technical audiences.
- Experience building training materials, scenario libraries, or detection rulebooks is a strong plus.
- Curiosity and analytical rigor to assess evolving financial crime typologies and adapt controls accordingly.
- Role type: Contractor, remote.
- Engagement focus: contribute to a customer project centered on the design and optimization of advanced financial-crime detection frameworks that will be used to train and evaluate AI systems.
- About the company: this work is with an AI data lab that transforms domain expertise into training data and evaluations to improve frontier AI models.
- Pay range: $50.00 to $90.00 per hour.
- Engagement is as an independent contractor. No prior AI experience is required, the role is centered on domain expertise in financial crime and AML.