Safeguards Policy Analyst, Fraud & Scams na Anthropic

Remoto - Remote-Friendly (Travel-Required), San Francisco, CA, New York City, NY

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The role of Safeguards Policy Analyst, Fraud & Scams at Anthropic involves designing and owning policies to mitigate fraud and scam-related harms on Anthropic's products. The analyst works closely with threat investigative, enforcement, engineering, and product teams to develop threat models, enforce policies, and collaborate across the organization. The position requires expertise in fraud typologies, threat modeling, policy creation, and cross‑functional communication, with a strong background in Trust & Safety within tech or AI contexts.

Salary

USD 245,000 - 285,000

Requirements

Skills

  • Trust & Safety experience with focus on fraud, scams, or financial crime in a tech or AI context
  • Experience writing, iterating on, and managing operational policies for fraud or abuse prevention at scale
  • Threat modeling for fraud and scam ecosystems (e.g., social engineering, romance scams, investment fraud, impersonation, phishing)
  • Ability to identify and articulate common fraud tactics and their manifestations on AI platforms
  • Proficiency in SQL or other data analysis tools to identify trends, measure enforcement efficacy, and surface policy gaps
  • Cross-functional collaboration with Engineering, ML, Legal, and Policy teams on safety initiatives
  • Experience working with generative AI products, including writing effective prompts for content review and enforcement use cases
  • Bachelor’s degree or equivalent combination of education, training, and/or experience
  • Fluency in English

Responsibilities

  • Draft, maintain, and iterate on Fraud & Scams policies governing Anthropic's products and APIs
  • Conduct structured policy reviews to identify gaps and lead process to close them
  • Develop threat models for fraud and scam vectors and translate them into enforceable policy language
  • Stay current on fraud and scam landscape, regulatory shifts, and threat actor TTPs
  • Design and architect automated enforcement systems and human review workflows
  • Review flagged content to drive enforcement decisions and surface policy improvements
  • Define and manage precision/recall tradeoffs in enforcement with data science teams
  • Build and maintain a feedback loop between threat intelligence, policy, and enforcement operations
  • Serve as primary policy point of contact for ML and Engineering teams developing fraud detection classifiers
  • Partner with Product, Engineering, and Data Science teams to optimize detection models and tooling
  • Collaborate with external researchers, law enforcement liaisons, and fraud SMEs
  • Educate internal stakeholders (Legal, Public Policy, Go-to-Market) on fraud policies and enforcement
  • Serve as an internal resource on fraud risk and brief leadership
  • Contribute to external communications and policy documentation related to fraud and platform integrity

Technologies

SQLGenerative AIMachine LearningData Science

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