Data Science Manager Integrity San Francisco
Classified Tasks (14)
Augment (7)
AI assists, human decides
Drive analytical and product strategy across policy enforcement, bot detection, fraud prevention, IP theft, risk measurement, and abuse prevention.
analytical
Balance near-term response efforts with the design and implementation of durable, scalable systems.
operational
Build and institutionalize metric frameworks, experimentation standards, monitoring and alerting systems, and repeatable evaluation approaches for Integrity interventions.
analytical
Translate ambiguous risk signals into actionable product and platform decisions.
analytical
Improve processes and create leverage through better tooling and AI-assisted workflows.
operational
Push the team toward an AI-leveraged operating mode by implementing modern tooling and model capabilities to accelerate detection, triage, analysis, and iteration.
technical
Design and build scalable systems to detect, measure, and mitigate emergent misuse patterns.
technical
Human-Only (7)
Requires human judgment
Lead and scale the Integrity Data Science team by hiring, coaching, and developing individual contributors and potential managers.
leadership
Lead data scientists working across trust & safety, fraud prevention, risk analysis, measurement, and modeling.
leadership
Build a high-performing Data Science function that keeps pace with fast-moving threats.
leadership
Partner with Product and Engineering to shape roadmaps and prioritize initiatives.
communication
Define ownership boundaries and evolve team structure and operating rhythms as the organization scales.
leadership
Support cross-organizational partners (e.g., Growth, Ads, GTM, Operations) where integrity risks intersect with product and business goals.
communication
Synthesize complex tradeoffs, surface risks, and communicate with senior leadership to drive alignment on priorities and success metrics.
communication