Job description

The Risk Intelligence team sits within Risk Detection and operates at the intersection of intelligence collection, analysis, and systems design. The team's mission is to move from primarily manual, reactive workflows toward scalable, data-driven, and proactive detection — working across first-party and third-party signals in close partnership with Product, Data Science, Engineering, and other Trust & Safety teams. This is a leadership role for someone who combines strong judgment, operational depth, and systems thinking. Reporting directly to the Global Head of Risk Detection, you will work in close partnership to shape priorities and raise the quality and scale of the function — bringing your own perspective and building the kind of trust that creates room to take on more over time. Responsibilities: - Lead, develop, and grow a high-performing Risk Intelligence team responsible for intelligence collection, analysis, and putting intelligence to work in support of proactive risk detection. - Translate team and organizational priorities into clear execution plans, operating mechanisms, and measurable outcomes. - Improve how intelligence is collected, structured, stored, and acted on — strengthening channels across first-party and third-party sources so signals more reliably inform detection and decision-making. - Work cross-functionally with Product, Engineering, and Data Science to improve detection inputs, data collection, internal tooling, reporting, and scalable intelligence workflows. - Identify operational gaps and drive improvements across the intelligence lifecycle, including opportunities to automate or augment workflows through structured data, rules, machine learning, and AI-enabled solutions where appropriate. - Define and track clear measures of impact, including improvements in detection quality, operational efficiency, and upstream prevention. - Build a healthy, high-standards team culture grounded in sound judgment, clear communication, strong partnership, and continuous improvement. Minimum Qualification(s): - 5+ years of experience in intelligence, risk, trust and safety, investigations, operations, product strategy, or related fields. - Experience managing and developing high-performing teams. - Experience leading complex, cross-functional work in fast-moving and ambiguous environments. - Excellent judgment and the ability to make thoughtful decisions in high-stakes or ambiguous situations. Strong analytical and quantitative skills, with the ability to use data to identify issues, prioritize opportunities, and inform decisions. - Strong communication and stakeholder management skills, including the ability to influence across a matrixed organization. - Demonstrated experience applying automation or AI-enabled solutions to improve how work gets done. - Demonstrated ability to improve systems, workflows, or operating models — not only execute within existing ones. Preferred Qualification(s): - Strong understanding of OSINT methodologies, online adversarial behavior, and intelligence-driven risk analysis. - Experience partnering closely with Product, Engineering, and Data Science to improve tools, workflows, or detection capabilities. - Experience leading a team through scale, process maturity, or capability-building inflection points. - Equally willing to share a dissenting view as to listen — you bring independent perspective and challenge assumptions constructively, including your own. - Comfort operating as a close partner to leadership — with the maturity to both align tightly and contribute independent perspective. - Experience in or adjacent to technology, government, media, law enforcement, national security, or related sectors.

Requirements

Must-haves

Lead, develop, and grow a high-performing Risk Intelligence team responsible for intelligence collection, analysis, and putting intelligence to work in support of proactive risk detection.
Translate team and organizational priorities into clear execution plans, operating mechanisms, and measurable outcomes.
Improve how intelligence is collected, structured, stored, and acted on — strengthening channels across first-party and third-party sources so signals more reliably inform detection and decision-making.
Work cross-functionally with Product, Engineering, and Data Science to improve detection inputs, data collection, internal tooling, reporting, and scalable intelligence workflows.
Define and track clear measures of impact, including improvements in detection quality, operational efficiency, and upstream prevention.
Build a healthy, high-standards team culture grounded in sound judgment, clear communication, strong partnership, and continuous improvement.
5+ years of experience in intelligence, risk, trust and safety, investigations, operations, product strategy, or related fields.
Experience managing and developing high-performing teams.
Experience leading complex, cross-functional work in fast-moving and ambiguous environments.
Strong communication and stakeholder management skills, including the ability to influence across a matrixed organization.
Demonstrated experience applying automation or AI-enabled solutions to improve how work gets done.
Demonstrated ability to improve systems, workflows, or operating models — not only execute within existing ones.
Strong understanding of OSINT methodologies, online adversarial behavior, and intelligence-driven risk analysis.
Experience partnering closely with Product, Engineering, and Data Science to improve tools, workflows, or detection capabilities.
Experience leading a team through scale, process maturity, or capability-building inflection points.
Equally willing to share a dissenting view as to listen — you bring independent perspective and challenge assumptions constructively, including your own.
Comfort operating as a close partner to leadership — with the maturity to both align tightly and contribute independent perspective.
Experience in or adjacent to technology, government, media, law enforcement, national security, or related sectors.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

machine learningai

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