Manager, Scaled Abuse Countermeasures and Research

EngineersOfAI; San Francisco (CA); On-site; USD 190,000 - 230,000; Full time

Job summary

Discord is looking for a Manager to lead the SCAR team in San Francisco, the platform's first line of defense against scaled abuse. You will set strategy, build a research program, and drive ML-powered automation to reduce manual work and close the loop with Safety ML.

You'll coach Scaled Abuse Scientists, define north-star metrics, and partner with Product, Data Science, Policy, Legal, Trust & Safety, and Revenue to bake safety into design decisions and harden the product against fraud and

Qualifications

• 2+ years of people management experience leading technical teams.
• 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.
• Strong analytical skills and fluency in SQL and Python for data investigation and pattern analysis.
• Excellent communication and cross-functional collaboration skills.

Responsibilities

• Lead and grow the SCAR team, a group of Scaled Abuse Scientists who defend against bulk fake accounts, login abuse, spam, scams, and fraud.
• Set a vision for automation and scale SCAR's impact by partnering with Safety ML on ML-driven detection and AI-powered incident response workflows.
• Define scaled abuse north-star metrics and build a roadmap and prioritization framework.
• Stand up a research program where the team operates as scientists to surface attacker questions and answer them through structured research.
• Close the loop with Safety ML so signals feed into model features and automated countermeasures.
• Partner cross-functionally with Product, Safety ML, Data Science, Policy, Legal, Trust & Safety, and Revenue to influence safety-by-design decisions.
• Coach, hire, and grow Scaled Abuse Scientists.
• Communicate attacker dynamics, economic incentives, and trade-offs clearly to senior leadership.

Skills

People management

Trust & Safety

ML/Automation

SQL

Python

Cross-functional collaboration

Communication

Job description

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 collaboration skills, with a history of partnering effectively across engineering, ML, data science, policy, legal, and product teams.
• A growth mindset: you seek feedback, reflect on decisions, and actively help your team do the same.

Bonus Points

• Experience leveraging LLMs or AI agents for incident response, investigation automation, or signal triage.
• Experience tackling scaled abuse problems at large social platforms, marketplaces, or other high-volume consumer products.
• Threat intelligence research backgroun