Safeguards Analyst, Account Abuse
San Francisco, CA | New York City, NYFull-TimeMid-levelAccounts / Finance
About Anthropic
- Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the Role
- Anthropic is an AI safety and research company working to build reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our customers and society as a whole. As a Safeguards Analyst focusing on Account Abuse, you will play a critical role in building and scaling the detection, enforcement, and operational capabilities that protect our platform against scaled abuse.
Responsibilities
- Develop and iterate on account signals and prevention frameworks that consolidate internal and external data into actionable abuse indicators
- Develop and optimize identity and account-linking signals using graph-based data infrastructure to detect coordinated and scaled account abuse
- Evaluate, integrate, and operationalize third-party vendor signals — assessing whether new data sources provide genuine lift in detection
- Expand internal account signals with new data sources and behavioral indicators to improve detection coverage
- Build and maintain processes that evaluate new product launches for scaled abuse risks, working closely with product teams to ensure enforcement readiness
- Operationalize and iterate on enforcement tooling — including appeals workflows, review processes, and user communications — to maintain quality and scale with growing volume
- Analyze enforcement performance through operational metrics, partnering with the team to keep detection accurate as abuse patterns evolve
- Manage payment fraud and dispute operations to protect revenue and maintain our standing with payment partners
- Coordinate enforcement efforts for policy compliance gaps across products, working with relevant teams to build scalable review processes
- Collaborate with cross-functional teams (Engineering, Product, Legal, Data Science) to surface new signals and translate detection capabilities into enforcement workflows
- Maintain detailed documentation of signal development, enforcement processes, and operational decisions
Qualifications
- 2+ years of experience in risk scoring, fraud detection, trust and safety, or policy enforcement
- Hands-on experience building detection systems, risk models, or enforcement processes and workflows
- Experience evaluating and integrating third-party data sources into detection or scoring pipelines
- Strong SQL and Python skills — this role involves heavy data analysis across complex, multi-table data relationships
- Familiarity with identity signals such as device fingerprinting, account linking, or entity resolution, or experience with appeals processes and customer-facing enforcement communications
- Demonstrated ability to analyze complex data problems and translate findings into actionable improvements
- Strong written and verbal communication skills — ability to explain technical tradeoffs and navigate cross-functional stakeholder conversations
- Equivalent practical experience or a Bachelor's degree in Computer Science, Data Science, or related field
You might be a good fit if you
- Have built risk scores, detection systems, signal pipelines, or enforcement processes in a previous role — identity verification, trust and safety, or similar
- Are comfortable working with ambiguous, noisy data and extracting meaningful signal
- Think critically about signal quality and enforcement performance — evaluating whether new detection signals or processes meaningfully improve outcomes
- Have experience with graph-based data, account-linking problems, or cross-functional process design
- Are proactive about identifying gaps in existing detection or enforcement and proposing new approaches
- Have experience leveraging generative AI tools to support analytical, detection, or enforcement workflows
- Can balance deep analytical work with cross-functional collaboration and stakeholder coordination
- Have a background or interest in cybersecurity or threat intelligence (a plus, not a requirement)
- The annual compensation range for this role is listed below.
- For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
How we're different
- We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
- The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
