About this role
Build a portfolio-wide platform that standardizes, governs, and distributes behavioral, identity, trust, safety, and enforcement signals. Create APIs, frameworks, data products, and adoption patterns that make signals easy for brands and central teams to discover, trust, integrate, and use. Partner with engineering and data science to evaluate signal quality, reliability, performance, drift, and business impact. Establish clear success metrics for the Signals Platform, including adoption, signal usage, fraud and abuse reduction, enforcement quality, operational efficiency, user quality, and MAU impact. Identify opportunities to use AI and ML to improve signal discovery, signal quality, anomaly detection, risk scoring, and decision support. Drive prioritization across competing signal needs, balancing brand-specific flexibility with portfolio-wide consistency and governance. Product leadership: 8+ years of product management experience, with demonstrated ownership of complex, technical, cross-functional products at Staff, Lead, or equivalent scope. Platform mindset: Proven ability to build shared services, data products, APIs, or platform capabilities used by multiple internal customers, business units, or brands. Trust & Safety, identity, risk, or data product experience: Background in Trust & Safety, fraud, abuse detection, identity, authenticity, compliance tooling, ML/data platforms, or risk systems preferred. Technical fluency: Comfort working with data infrastructure, APIs, ML models, signals, risk scoring, data quality, observability, and platform architecture concepts. AI fluency: Ability to identify practical AI use cases, evaluate AI-supported product opportunities, and partner with technical teams to build responsible, measurable AI-enabled capabilities. Strategic and execution balance: Ability to set a clear long-term vision while driving near-term delivery, adoption, and measurable business outcomes. Cross-functional influence: Strong ability to influence without direct authority across engineering, data science, operations, compliance, legal, brand product teams, and senior stakeholders. Customer orientation: Experience running discovery with internal customers, translating user and operational needs into product strategy, and building products that teams actively adopt. Analytical rigor: Strong ability to define success metrics, analyze performance, evaluate tradeoffs, and communicate product impact through data. Operational discipline: Ability to create durable product operating models, including intake, prioritization, roadmap planning, documentation, launch readiness, adoption tracking, and ongoing performance monitoring. Communication: Excellent written and verbal communication skills, with the ability to simplify complex technical topics for executive, operational, and brand audiences.