Data Science Manager, Integrity

In this role, you will:

• Lead and scale a high-impact Integrity Data Science team—hiring, coaching, and developing DS ICs (and potentially future managers) while setting a strong technical and cultural bar.
• Drive strategy across multiple Integrity domains (policy enforcement, bot detection, fraud prevention, IP theft, risk measurement, abuse prevention), balancing near-term response with durable systems.
• Build and institutionalize analytical rigor: clear metric frameworks, experimentation standards, monitoring/alerting, and repeatable evaluation approaches for Integrity interventions.
• Partner deeply with Product & Engineering to shape roadmaps, prioritize the right bets, and translate ambiguous risk signals into practical product and platform decisions.
• Evolve team structure and operating model as the org scales—defining ownership boundaries, improving processes, and creating leverage through better tooling and AI-assisted workflows.
• Enable cross-org outcomes, supporting partners outside Integrity (e.g., Growth, Ads, GTM) where integrity risks intersect with product and business goals.
• Communicate clearly with senior leadership, synthesizing complex tradeoffs, surfacing risk, and driving alignment on priorities and success metrics.
• Push the team toward an AI-leveraged operating mode, using modern tooling and model capabilities to accelerate detection, triage, analysis, and iteration.

You might thrive in this role if you:

• Have deep experience leading and scaling Data Science teams, ideally in trust & safety, fraud/abuse, security, risk, or other adversarial problem spaces in fast-moving environments.
• Bring strong technical grounding across modern DS techniques (experimentation, causal inference, anomaly detection, risk modeling, measurement design) and can coach others to execute with rigor.
• Have a track record of building durable partnerships across DS, Engineering, Product, and Operations—able to influence without authority and create shared accountability.
• Are excellent at hiring, mentoring, and developing technical talent, and can build a culture that is both high-bar and supportive.
• Can translate messy, evolving threats into clear frameworks, metrics, and decisions—and keep the team focused on the highest-leverage work.
• Are comfortable operating in ambiguity, and can bring structure, clarity, and momentum where the “right answer” isn’t obvious.

Bonus if you:

• Have experience deploying scaled detection solutions using LLMs, embeddings, fine-tuning, or related ML systems for abuse/fraud/risk.
• Have worked closely with policy, content moderation, investigations, or security operations teams and understand how to design analytics that actually works end-to-end.
• Have built or led measurement systems that balance safety, user experience, and operational/business constraints.