Manager, Scaled Abuse Countermeasures and Research

Discord Discord · Consumer · San Francisco, CA · Machine Learning

Manager for Scaled Abuse Countermeasures and Research (SCAR) team at Discord. This role will lead and grow the team, focusing on ML and AI-powered automation for scaled abuse detection (fake accounts, login abuse, spam, scams, fraud). Responsibilities include setting team vision, defining metrics, establishing a research program, and closing the loop with Safety ML for model improvements. Requires people management experience, Trust & Safety background, and ability to drive ML/automation adoption. Experience with LLMs/AI agents is a plus.

What you'd actually do

  1. 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.
  2. 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.
  3. Define scaled abuse north-star metrics and build a roadmap and prioritization framework that keeps the team focused on the highest-impact problems.
  4. 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.
  5. 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.

Skills

Required

  • 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
  • Ability to think from first principles and apply behavioral-economics reasoning to adversarial systems
  • Excellent communication and cross-functional collaboration skills

Nice to have

  • 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 background
  • A relevant degree in Computer Science, Machine Learning, Statistics, or a related quantitative field, or equivalent practical experience

What the JD emphasized

  • ML and AI-powered automation
  • ML-driven detection
  • AI-powered incident response workflows
  • structured research program
  • ML features and pipeline upgrades
  • automated countermeasures

Other signals

  • ML-driven detection
  • AI-powered incident response workflows
  • structured research program
  • attacker operations and signals
  • ML features and pipeline upgrades