Manager, Scaled Abuse Countermeasures and Research

Discord · San Francisco Bay Area

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Role at a Glance

Discord is hiring a manager to lead SCAR — its scaled-abuse response and research team covering fake accounts, login abuse, spam, scams, and fraud at consumer scale. The mandate is explicitly automation-first: replace manual workflows with ML-driven detection and AI-assisted incident response. Requirements: 4+ years in adversarial trust & safety, 2+ years managing technical teams. Base salary: $220,000–$275,000 plus equity. On-site, San Francisco Bay Area.

What This Role Is About

This is a leadership position at the intersection of defensive security operations and applied research. You would oversee a team of abuse scientists who identify and neutralize high-volume threats on Discord's platform, combining rapid incident response with structured investigation of attacker behavior. The strategic mandate includes transitioning the team away from manual playbooks toward ML-driven detection and AI-assisted automation. You would report directly to the Director of Safety Automation and hold meaningful influence over roadmap, research program design, and how frontline signals feed back into machine-learning pipelines.

About Discord

Discord is a communication platform built around gaming and shared interests, with tens of millions of daily active users connecting over everything from competitive esports to neighborhood hobby groups. Unlike passive content platforms, Discord centers on ongoing relationships and real-time conversation — before, during, and after play. Headquartered in San Francisco, the company's Safety Automation function is a critical investment: the larger and more engaged a community platform grows, the more sophisticated the abuse targeting it becomes. This team sits at the front of that fight.

What You Will Own

  • Lead and grow the SCAR team — a group of Scaled Abuse Scientists who serve as Discord's primary defense against fake account creation, login abuse, spam, scams, and high-volume fraud.
  • Drive an automation-first vision by partnering with the Safety ML team to build ML-powered detection pipelines and AI-assisted incident response workflows that reduce reliance on manual intervention.
  • Define north-star metrics for scaled abuse and maintain a prioritized roadmap that keeps the team focused on the highest-impact threat categories.
  • Establish a structured research program where the team operates like scientists — surfacing open questions about attacker operations and answering them through systematic experimentation and analysis.
  • Close the signal loop between SCAR and Safety ML so that team findings feed directly into model features and pipeline upgrades, converting tactical wins into durable, automated defenses.
  • Collaborate cross-functionally with Product, Data Science, Policy, Legal, Revenue, and Trust & Safety to shape safety-by-design decisions upstream before abuse can occur.
  • Hire, coach, and develop Scaled Abuse Scientists — setting clear performance expectations and meaningful growth paths.
  • Translate attacker dynamics, economic incentives, and strategic trade-offs into clear narratives for senior leadership.

Must-Have Qualifications

  • 2+ years of people management experience leading technical teams — engineers, ML engineers, data scientists, or applied researchers — or an equivalent track record of coordinating and mentoring technical work at this level.
  • 4+ years of hands-on experience in Trust & Safety, fraud prevention, 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 — model-building is not required, but evaluating model quality and steering development toward automated outcomes is essential.
  • Working proficiency in SQL and Python for data investigation and pattern analysis; full software-engineering depth is explicitly not required.
  • Analytical first-principles thinking applied to adversarial systems: identifying attacker incentives and determining the most cost-effective ways to break their economics.
  • Strong cross-functional collaboration history — documented track record of effective partnership across engineering, ML, data science, policy, legal, and product organizations.
  • Growth mindset: consistently seeks and integrates feedback, reflects on decisions, and actively encourages the same habits in direct reports.

Bonus Qualifications

  • Hands-on experience using LLMs or AI agents for incident response, investigation automation, or signal triage workflows.
  • Prior exposure to scaled abuse problems at large social platforms, consumer marketplaces, or similarly high-volume consumer products.
  • Threat intelligence background, including knowledge of internet infrastructure and the toolkits and techniques adversaries deploy at scale.
  • Genuine enthusiasm for Discord and gaming culture, and an understanding of the communities the platform serves.
  • Degree in Computer Science, Machine Learning, Statistics, or a related quantitative field — or equivalent depth built through practical experience.

Skills Breakdown: Required vs. Preferred

Hard requirements center on data fluency (SQL and Python for investigation work) and the ability to evaluate and steer machine learning development without personally writing models. Adversarial Trust & Safety or anti-abuse experience at consumer scale is non-negotiable, as is people-management experience over technical teams. Nice-to-haves extend the ML angle into LLMs and AI-agent workflows and add threat intelligence tradecraft on top. This is a senior people-leadership and strategy role — communication clarity, roadmap ownership, and cross-functional influence carry as much weight as technical depth.

Salary and Compensation

The posted US base salary range is $220,000 to $275,000 per year. The offer also includes equity and a benefits package; specific benefit details are not listed in the job posting. Pay within the stated band is determined by skills, experience, and relevant education or training. Note that this salary figure covers base compensation only — equity and benefits are additional components not reflected in that number. No information on signing bonuses, stock vesting schedules, or specific benefits was included in the posting.

Location and Work Arrangement

This role requires candidates to live in or be willing to relocate to the San Francisco Bay Area, which Discord defines as Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties. Relocation assistance may be available. The posting does not indicate remote or hybrid options for this position. Visa sponsorship eligibility is not addressed in the job description.

Frequently asked questions

Is this role remote or hybrid?

No. The posting explicitly requires candidates to reside in or be willing to relocate to the San Francisco Bay Area. No remote or hybrid arrangement is indicated.

Do I need to build machine learning models to qualify?

No. The stated requirement is the ability to evaluate model quality and direct ML development toward automated outcomes — hands-on model building is not expected or required.

What is the salary for this position?

The posted US base salary range is $220,000 to $275,000 per year, plus equity and benefits. Final pay within that band depends on skills, experience, and relevant education or training. The posted figure covers base salary only.

What team would I be managing?

You would lead the Scaled Abuse Countermeasures and Research (SCAR) team — a group of Scaled Abuse Scientists responsible for incident response and threat research targeting fake accounts, login abuse, spam, scams, and fraud at consumer scale.

Is a specific degree required for this role?

No. A degree is not listed as a hard requirement. A background in Computer Science, Machine Learning, Statistics, or a quantitative field appears as a bonus qualification only, with equivalent practical experience explicitly accepted.

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