Head of Data Science - Trust and Safety

The Trust & Safety Data Science team s mission is to provide strategic and analytical support that enables TikTok to be the most trusted platform for our users and creators. The team partners with various functions across the organization - including Policy, Risk Prevention & Response, and Transparency Reporting, among others - to drive operational excellence through data. Its charter is to establish shared success metrics, develop trusted insights, and enable strategic decision-making across the organization.

Responsibilities:

• Lead and define the global Data Science strategy for the Trust & Safety organization, ensuring alignment with business priorities and long-term company objectives.
• Build, develop, and lead high-performing teams of Data Scientists across multiple regions.
• Partner closely with Product, Engineering, Policy, Operations and executive leadership to translate business challenges into scalable data-driven solutions.
• Define and evolve the organization s measurement framework, including north-star metrics, experimentation strategy, and operational KPIs.
• Drive the development of advanced analytics, machine learning, forecasting, and optimization models that improve Trust & Safety decision-making and operational effectiveness.
• Establish a strong data foundation by improving data quality, governance, observability, and measurement consistency across the organization.
• Deliver executive-level insights through clear storytelling, influencing strategic investments and business priorities.
• Champion an AI-first approach by identifying opportunities to leverage automation, GenAI, and predictive analytics across Trust & Safety workflows.
• Foster a culture of technical excellence, innovation, collaboration, and continuous learning while attracting and developing world-class talent.
• Represent the Data Science organization as a trusted strategic partner across global cross-functional leadership teams. Minimum Qualification(s):
• Bachelor s degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or another quantitative discipline, or equivalent practical experience.
• 5+ years of experience in Data Science, Machine Learning, Analytics, or a related quantitative field.
• 5+ years of experience leading and developing global Data Science or Analytics organizations within a technology company.
• Demonstrated experience defining and executing organization-wide data strategies that influence product and business decisions.
• Strong expertise in statistical analysis, experimentation, machine learning, and large-scale data analytics.
• Experience working with large-scale distributed data platforms and modern analytical technologies (e.g., SQL, Python, Spark, Hadoop, cloud data platforms).
• Proven ability to communicate complex technical concepts and analytical insights to executive leadership and influence strategic decisions.

Preferred Qualification(s):

• Master s or PhD in Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative discipline.
• Experience leading Data Science organizations supporting Trust & Safety, Integrity, Risk, Fraud, Security, or other large-scale online platform ecosystems.
• Experience building AI-powered decision systems, including predictive analytics, GenAI, or LLM-enabled products.
• Strong understanding of experimentation frameworks, causal inference, and large-scale measurement systems.
• Experience driving organizational transformation through data governance, observability, and operational excellence initiatives.
• Demonstrated success leading globally distributed teams across multiple regions and time zones.
• Track record of influencing executives and driving company-wide strategic initiatives through data.
• Experience partnering closely with Product, Engineering, and Policy organizations to deliver measurable business outcomes.
• Proven ability to attract, develop, and retain world-class technical leadership talent.
• Passion for building safe, trustworthy, and responsible technology platforms.