Applied Research Scientist - Trust and Safety

The Applied Research Scientist will drive rigorous research to deepen our understanding of complex Trust & Safety challenges and inform better policy, product, and operational decisions. This role combines quantitative analysis, qualitative research, and domain expertise to uncover emerging risks, evaluate safety interventions, and translate insights into actionable strategies. The researcher will partner closely with Data Science, Policy, Product, Operations, and Engineering teams to shape how we understand and address evolving safety challenges at scale.

Responsibilities

Conduct Mixed-Methods Research on Complex Safety Problems: - Lead end-to-end research initiatives, from problem framing and hypothesis development to analysis, validation, and recommendations. - Apply quantitative methods including statistical analysis, experimentation, causal inference, and modeling to identify trends, measure impact, and evaluate interventions. - Apply qualitative methods including user research, case analysis, stakeholder interviews, and ecosystem research to understand behaviors, motivations, and emerging risks. - Develop research frameworks to measure safety outcomes, policy effectiveness, enforcement quality, and user impact.

Translate Research into Policy and Safety Insights:

• Analyze large-scale behavioral, operational, and enforcement data to uncover risk patterns and opportunities for intervention.
• Investigate the underlying drivers behind quantitative signals through qualitative evidence and domain understanding.
• Partner with Policy teams to evaluate existing policies, identify gaps, and provide evidence-based recommendations for policy evolution.
• Assess the effectiveness and unintended consequences of safety interventions, balancing enforcement goals, user experience, and ecosystem health.
• Translate complex findings into clear narratives and recommendations for stakeholders.

Drive Research Excellence and Cross-Functional Impact:

• Partner with Product, Engineering, Operations, and Policy teams to influence safety strategy and decision-making.
• Build reusable research methodologies, measurement frameworks, and analytical approaches across T&S.
• Challenge assumptions and bring rigorous evidence into ambiguous, high-impact safety decisions.
• Contribute to raising research standards and capabilities across the T&S Data Science organization.