We are seeking an experienced Data Scientist to join the Entity & Actor Integrity team within Meta's Trust & Safety pillar. This team is responsible for protecting creators and users from account compromise and impersonation attacks. You will drive data-driven strategies to detect, prevent, and mitigate creator compromise and creator impersonation at scale, working closely with cross-functional partners to build safer experiences across Meta's platforms.
Responsibilities
Develop and refine detection models and metrics for identifying creator compromise and impersonation patterns at scale Partner with product, engineering, and policy teams to design and evaluate integrity interventions that protect creators Conduct deep-dive analyses to understand adversarial behaviors, attack vectors, and emerging threats targeting high-value accounts Define success metrics, build dashboards, and create measurement frameworks to track integrity health and intervention effectiveness Design and analyze experiments to optimize detection precision and user friction trade-offs Communicate insights and recommendations to leadership to inform Trust & Safety strategy and investment decisions Collaborate across integrity teams to identify cross-cutting opportunities and share learnings on actor-based abuse patterns
Qualifications
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field 10+ years of experience in quantitative analysis, data science, or related analytical roles Experience with data querying languages (e.g., SQL) and scripting languages (e.g., Python, R) Experience communicating complex analytical findings to leadership and cross-functional stakeholders Experience leading ambiguous, cross-functional analytics projects with multiple stakeholders Familiarity with machine learning approaches for classification and anomaly detection Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience in Trust & Safety, integrity, fraud detection, or security-related analytics Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience with adversarial analysis, abuse detection, or account security domains Experience building and evaluating detection systems or intervention mechanisms