Manager, Safety Analytics

Discord•San Francisco, CA

11d•$220,000 - $275,000•Onsite

About The Position

Discord is seeking an Analytics Manager to lead its Scaled Abuse Countermeasures and Research (SCAR) team. This team is responsible for safeguarding Discord's platform integrity by detecting, analyzing, and disrupting high-volume threats through automated systems, research, and incident response. The role reports to the Head of Safety Intelligence and Automation. Discord aims to give people the power to create spaces for belonging and build genuine relationships, playing a significant role in the future of gaming.

Requirements

2+ years of people management experience leading technical teams (engineers, data scientists, analysts, applied researchers, or equivalent).
4+ years of experience in a Trust & Safety domain (fraud, spam, scams, account compromise, or other high-volume threats).
Fluency in SQL and/or Python for data investigation and pattern analysis.
Strong analytical problem-solving skills, with expertise in measurement and experimentation.
Demonstrated ability to drive automation adoption in operations or incident response workflows to increase team leverage and reduce manual work.
Excellent communication and cross-functional collaboration skills, with the ability to translate complex technical topics into clear takeaways for senior leadership.

Nice To Haves

Experience leveraging LLMs or AI agents for incident response, investigation automation, or signal triage.
Experience tackling scaled abuse at large social platforms, marketplaces, or other high-volume consumer products.
Threat intelligence research background, including understanding of internet infrastructure and attacker tools/techniques.
A strong passion for Discord and/or gaming, and an appreciation for the communities served.
A relevant degree in Computer Science, Machine Learning, Statistics, or a related quantitative field, or equivalent practical experience.

Responsibilities

Lead and mentor a team of data analysts, scientists, and researchers investigating active threats, identifying platform abuse vectors, and uncovering adversarial patterns.
Define a strategic roadmap to prioritize and disrupt high-impact abuse operations through structured research, rigorous analyses, and live experimentation.
Collaborate with the safety machine learning team to enhance models by identifying threat signals for automated countermeasures.
Partner cross-functionally with Product, Engineering, Data Science, Policy, Legal, and Revenue to influence safety-by-design decisions.
Influence capacity towards high-impact infrastructure, such as automated rule engines, ML models, or agent moderation tools.