Manager, Trust Business Intelligence & Insights at LinkedIn3

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. This role will be hybrid in LinkedIn's Mountain View campus. The Trust Business Intelligence & Insights Manager is a cross-functional leadership role that blends data science, data management, analytics, and strategy to create impact at global scale. You will lead a talented team of analysts while partnering closely with product, trust, engineering, policy, and data science teams. Together, you’ll build models and insights that help keep members and our platform safe. Responsibilities Leadership: • Partner with teams in, Product, Engineering, Policy, Finance, and Operations to identify new opportunities, challenge assumptions, and align data-driven goals , driving transformative outcomes across Trust. • Define and execute a multi-year vision for Trust Ops Data initiatives supporting LinkedIn’s trust and operational goals. • Lead and develop high-performing teams of analysts across geographies; mentor senior talent and foster a culture of excellence, inclusion, and craftsmanship. • Collaborate with engineering and data science teams to shape data platform evolution enabling scale. Technical Execution • Leverage the world’s richest professional dataset to uncover insights that improve member engagement, marketplace integrity, and business growth. • Develop advanced models, causal inference frameworks, and experiments to evaluate new features, trust defenses, and understand impact of efficiencies. • Build and maintain data pipelines, metrics, dashboards, and insights to enable data-driven decisions across LinkedIn. • Lead technical reviews, ensure data and code quality, and define engineering best practices for data systems operating at massive scale. • Translate analytical findings into clear, compelling narratives that influence executive decision-making. • Develop compelling data visualizations and narratives that translate complex data into clear, actionable insights for diverse audiences.