Risk Analyst, Global Response Operations

The Protect team within Global Response Operations is focused on detecting emerging on-platform risks that pose harm to our community and businesses on our platform. We identify, investigate and understand those risks. We partner closely with other Global Response Operations teams, Policy, Product and Process teams to mitigate those risks.

We are looking for someone who has a passion for identifying risks and investigating to understand where and how these are manifesting on our platforms. This individual has a demonstrated capacity to leverage data and AI tools to both detect emerging risks and investigate them at scale. They are comfortable building and iterating on automated workflows, prototyping AI-powered solutions, and using LLM-based tools to accelerate detection and investigation. A successful candidate has demonstrated experience conducting structured investigations, including evidence gathering, root cause analysis, and documentation of findings, is effective in ambiguous situations, and brings a builder's mindset - we are looking for a self-starter who is excited to help us shape the future of AI-native detection work and processes.

This role may involve exposure to potentially graphic and/or objectionable content including but not limited to graphic images, videos, audio and text, offensive or derogatory language, and other potential objectionable material, such as child exploitation, graphic violence, self-injury, animal abuse, and other content which may be considered offensive or disturbing.

Responsibilities

Drive the scoping and development of risk signals for key problem areas/abuses, including building automated detection pipelines and AI-powered signal aggregation
Identify emerging risks using on-platform and off-platform signals, through monitoring, analysis, and AI-assisted pattern recognition
Conduct investigations to develop rigorous understanding and knowledge of potential emerging trends and evolving risks in priority areas
Work cross-functionally to drive mitigation for identified risk areas, including conducting enforcement on violating trends
Build and execute risk detection strategies to support the management of critical events, such as elections and crises
Use data, internal tools, and AI agents to identify and investigate potential risk areas and patterns at scale and across abuse types
Use quantitative and qualitative research methods to perform root cause analyses on investigative findings or high-priority escalations
Partner with internal experts to build a rigorous understanding of how, where, and why broad forms of abuse are experienced across the platform
Synthesize investigative findings through the creation of analysis and presentations that provide a succinct, coherent narrative assessing risk
Build, prototype, and iterate on AI-native tools and workflows that improve detection capabilities - including agent prototypes, automated investigation workflows, and LLM-powered analysis tools. Champion adoption of technical solutions that drive efficiency, speed, and reduction of language dependence

Qualifications

Bachelor's degree or equivalent experience in investigations, data analytics or technical systems roles
4+ years experience in investigations, data analytics or technical systems roles in Trust & Safety or Risk Operations
Analytical thinking and problem-solving experience
Proficiency in SQL and comfort using AI-assisted tools (e.g., LLMs, code assistants) to accelerate data analysis and workflow automation
Experience working with complex data sets and aptitude for risk identification and analysis using data skills
Experience communicating progress and outputs to both technical and non-technical audiences
Experience prioritizing multiple functions and tasks
Ability to work with potentially graphic and objectionable content Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Experience investigating Ads, eCommerce, payments, financial risks
Experience with prompt engineering, LLM-based tools, or workflow automation platforms
Proficiency in Python, with experience using it for automation, scripting, or building lightweight tools
Demonstrated ability to rapidly prototype solutions - comfort with a 'build, test, iterate' approach to tooling
Experience building and operationalizing AI agents, automated workflows, or detection pipelines
Experience in risk signal analysis and investigations
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)