Data Scientist

• Define the measurement framework for user-level risk across products and cohorts: scope the questions that matter and align on clear, policy-grounded definitions
• Establish baselines and statistical confidence for core metrics: prevalence, intensity, trends, and cohort dynamics
• Build decision-ready reporting surfaces: executive dashboards, weekly briefs, and launch readouts that translate insights into action
• Clean and organize ambiguous data from disparate sources, with an eye toward building automated pipelines and systems
• Create attribution and change-tracking: connect shifts in user behavior to mitigations, product changes, and external events
• Partner across Safety Systems, Data Science, Integrity, Product, and Policy: ensure one coherent analytics entry point and consistent standards
• Uphold quality, privacy, and governance: document methods, ensure auditability, and maintain durable measurement hygiene
• Monitor signals for emerging risks and anomalies: recommend priorities that reduce harmful usage and improve user safety
• Communicate clearly and concisely: deliver insights and trade-offs to executives and engineering teams in language that drives decisions

Data Scientist – User Risk Measurement

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