Director of Data Science, Trust & Safety, Signals and Content Understanding

Lead a high-impact data science organization focused on trust & safety, user understanding, and content understanding at scale. Define a multi-year strategy and roadmap with north-star outcomes and leading indicators that predict risk and improve quality. Operationalize leading indicators by instrumenting input metrics such as policy signals, spam/abuse rates, account authenticity, coverage, latency, and evaluation accuracy. Build, mentor, and grow a world-class team of data science managers and senior ICs spanning analytics, ML evaluation, experimentation, and causal inference. Partner with Product, Engineering, and Policy to translate complex trust questions into shipped ML capabilities with measurable impact on detection, enforcement, and distribution. Own measurement and decision quality through causal inference, experimentation, offline evaluation, and long-term value assessment to balance safety with user experience.