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Salary: USD 220,000 - 275,000 / annual
Discord is seeking a Manager of Safety Analytics to lead the Scaled Abuse Countermeasures and Research (SCAR) team, which safeguards platform integrity by detecting, analyzing, and disrupting high-volume threats through automated systems, deep research, and active incident response.
In this role, you will lead and mentor a team of data analysts, scientists, and researchers investigating active threats, identifying platform abuse vectors, and uncovering adversarial patterns. You'll define a strategic roadmap that prioritizes and disrupts the highest-impact abuse operations through structured research, rigorous analysis, and live experimentation. Close collaboration with the safety machine learning team will help improve models by identifying threat signals that translate into long-term, automated countermeasures.
Key responsibilities include cross-functional partnership with Product, Engineering, Data Science, Policy, Legal, and Revenue teams to influence safety-by-design decisions upstream of abuse. You'll drive capacity toward high-impact infrastructure such as automated rule engines, ML models, and agent moderation tools.
Required qualifications include 2+ years of people management experience leading technical teams (engineers, data scientists, analysts, applied researchers), 4+ years in Trust & Safety domains (fraud, spam, scams, account compromise, or similar high-volume threats), and fluency in SQL and/or Python for data investigation and pattern analysis. Strong analytical problem-solving skills, expertise in measurement and experimentation, and demonstrated ability to drive automation adoption are essential. Excellent communication and cross-functional collaboration skills are required to translate complex technical topics for senior leadership.
Bonus qualifications include experience leveraging LLMs or AI agents for incident response, tackling scaled abuse at large social platforms or marketplaces, threat intelligence research background, passion for Discord and gaming communities, and relevant degrees in Computer Science, Machine Learning, Statistics, or related quantitative fields.
Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.
