# Safeguards Policy Analyst, Fraud & Scams

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA, New York, NY
**Role:** Other
**Salary:** $245k – $285k/yr
**Skills:** SQL, Threat Modeling, Machine Learning Classifiers, Data Analysis, Generative AI, Aml/Kyc, Policy Design, Fraud Detection, Precision/Recall Tuning, Social Engineering Detection
**Posted:** 2026-04-07

> Designs and owns fraud & scams policies, builds scalable enforcement workflows, and collaborates with ML/Engineering teams to detect/mitigate threats on AI products. Requires Trust & Safety experience in fraud, policy iteration, and cross-functional collaboration in fast-paced environments.

## Job Description

## Responsibilities

### Policy Design & Ownership
- Draft, maintain, and iterate on Fraud & Scams policies governing Anthropic's products and APIs, with clarity for both model enforcement and human reviewers
- Conduct regular structured policy reviews to identify gaps, ambiguities, and coverage failures, and lead the process to close them
- Develop detailed threat models for fraud and scam vectors — including social engineering, financial fraud, impersonation scams, phishing, and AI-enabled fraud — and translate these into enforceable policy language
- Stay current on the fraud and scam landscape, including emerging typologies, regulatory shifts, and threat actor tactics, techniques, and procedures (TTPs)

### Enforcement Strategy & Operations
- Design and architect automated enforcement systems and human review workflows that scale effectively while maintaining high precision and recall
- Review flagged content to drive enforcement decisions and surface policy improvements grounded in real-world cases
- Define and manage precision/recall tradeoffs in enforcement, working with data science teams to continuously tune classifiers and detection signals
- Build and maintain an effective feedback loop between threat intelligence, policy, and enforcement operations to ensure timely response to novel and evolving fraud threats

### Technical & Cross-functional Collaboration
- Serve as the primary policy point of contact for ML and Engineering teams developing fraud detection classifiers, working to translate policy intent into technical artifacts and training signals
- Partner with Product, Engineering, and Data Science teams to optimize detection models, automated enforcement pipelines, and tooling for fraud-specific policy violations
- Collaborate with external researchers, law enforcement liaisons, and fraud SMEs to gather feedback on policy effectiveness and emerging risk areas

### Stakeholder Alignment & Education
- Educate and align internal stakeholders — including Legal, Public Policy, and Go-to-Market teams — around Anthropic's fraud and scams policies and enforcement approach
- Serve as an internal resource on fraud risk, briefing leadership and cross-functional partners as threats evolve
- Contribute to Anthropic's external communications and policy documentation related to fraud and platform integrity where relevant

## You may be a good fit if you have experience
- Working as a Trust & Safety professional with a focused background in fraud, scams, or financial crime — particularly in a tech platform or AI context
- Writing, iterating on, and managing operational policies for fraud or abuse prevention at scale
- Threat modeling for fraud and scam ecosystems, including social engineering, romance scams, investment fraud, impersonation, and phishing
- Identifying and articulating common fraud tactics (e.g., pig butchering, advance fee fraud, account takeover facilitation) and how they manifest on AI platforms
- Using **SQL** or other data analysis tools to identify trends, measure enforcement efficacy, and surface policy gaps
- Collaborating cross-functionally with Engineering, ML, Legal, and Policy teams on safety initiatives
- Working with generative AI products, including writing effective prompts for content review and enforcement use cases
- Thriving in a fast-paced, ambiguous environment where priorities shift and the threat landscape evolves rapidly

## Preferred Qualifications
- Experience at a major technology platform, financial institution, or fraud intelligence firm in a policy, operations, or investigative capacity
- Familiarity with the generative AI risk landscape and how large language models can be exploited for fraud and social engineering
- Background in threat intelligence, financial crimes compliance (**AML/KYC**), or law enforcement focused on cyber-enabled fraud
- Demonstrated ability to develop and communicate policy positions to diverse stakeholders including legal counsel and executive leadership

## Compensation
**Annual Salary: $245,000—$285,000 USD**

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