Manager, Scaled Abuse Countermeasures and Research

Discord·San Francisco Bay Areasenior

In short

→Liderar un equipo que combate abuso a gran escala en Discord, como cuenta falsa en masa y spam.
→Trabajar con IA y machine learning para automatizar respuestas y mejorar detección, reduciendo tareas manuales.
→Destacar por proponer investigación estructurada y enfoque científico para entender tácticas de atacantes.

Fluency in English required.

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What they ask for

✓2+ años liderando equipos técnicos (ingenieros, científicos de datos, ML).
✓4+ años en Trust & Safety, fraude o anti-abuso en plataformas de consumo a gran escala.
✓Experiencia comprobada en impulsar adopción de ML y automatización en seguridad.
✓Habilidad analítica con dominio de SQL y Python para análisis de datos.
✓Razonamiento basado en primeros principios y economía del comportamiento adversarial.
✓Capacidad para comunicar dinámicas de atacantes y decisiones estratégicas a liderazgo.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

MLAISQLPythonSafety MLData ScienceTrust & SafetyPolicyLegalRevenue

Who should you write to at Discord?

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Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games. Discord exists to give people the power to create space to find belonging — to talk regularly with the people they care about and build genuine relationships with friends and communities close to home or around the world. We re looking for a Manager to lead our Scaled Abuse Countermeasures and Research (SCAR) team — Discord s first line of defense against scaled abuse. SCAR combines rapid incident response with deep threat research and signal generation across bulk fake account creation, login abuse, spam, scams, fraud, and other high-volume threats. This is an opportunity to reshape how the team operates: set a sharper strategy, stand up a structured research program, and lean heavily into ML and AI-powered automation to replace today s manual workflows. This role reports to the Director of Safety Automation. What You ll Be Doing • Lead and grow the SCAR team, a group of Scaled Abuse Scientists who serve as Discord s first line of defense against bulk fake account creation, login abuse, spam, scams, fraud, and other high-volume threats. • Set a vision for the team that leans heavily into automation — scale SCAR s impact by partnering with Safety ML on ML-driven detection and building AI-powered incident response workflows that increase the team s leverage and reduce manual work. • Define scaled abuse north-star metrics and build a roadmap and prioritization framework that keeps the team focused on the highest-impact problems. • Stand up a research program where the team operates as scientists: surface the most important questions about attacker operations and signals, then systematically answer them through structured research and experimentation. • Close the loop with Safety ML so that SCAR s signals feed directly into model features and pipeline upgrades, and tactical wins translate into long-term, automated countermeasures. • Partner cross-functionally with Product, Safety ML, Data Science, Policy, Legal, Trust & Safety, and Revenue, influencing safety-by-design decisions upstream so abuse is prevented, not just mitigated. • Coach, hire, and grow Scaled Abuse Scientists. • Communicate attacker dynamics, economic incentives, and trade-offs clearly to senior leadership. What you should have • 2+ years of people management experience leading technical teams, including engineers, ML engineers, data scientists, or applied researchers, or an equivalent track record of leading, mentoring, or coordinating technical work in a way that has prepared you to step into this role. • 4+ years of experience working on Trust & Safety, fraud, anti-abuse, or a closely adjacent adversarial domain at a consumer-scale platform. • Demonstrated ability to drive ML and automation adoption within a Trust & Safety or operations context. You don t need to build models yourself, but you need to understand them well enough to evaluate their quality, direct their development, and push a team toward automated solutions. • Strong analytical skills and fluency in SQL and Python for data investigation and pattern analysis (not full software engineering proficiency required). • Ability to think from first principles and apply behavioral-economics reasoning to adversarial systems: why are attackers doing this, what are the incentives, and what is the most cost-effective way to break their economics. • Excellent communication and cross-functional collabo

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