Data Scientist, Transparency & Observability - Trust and Safety

TikTok's Trust & Safety team works to create a safe and trusted platform for billions of people around the world. We combine policy, technology, and operations to detect harmful content, protect users, and promote healthy online communities.

The Transparency & Observability Data Science team builds the data, metrics, and analytical capabilities that help us understand how our enforcement systems perform. Our work supports both internal decision-making and external transparency reporting, while improving the reliability, explainability, and quality of Trust & Safety data.

As a Data Scientist on this team, you will develop scalable metrics, monitoring systems, and analytical solutions that provide greater visibility into platform safety and help drive continuous improvements.

Responsibilities: - Build Trust & Safety Metrics & Monitoring: - Design and develop metrics that measure Trust & Safety enforcement across different products and content types. - Build dashboards and monitoring solutions that provide actionable insights into platform safety. - Develop automated anomaly detection and alerting to identify data or operational issues early. - Improve Data Quality: - Help ensure Trust & Safety data is accurate, reliable, and delivered on time. - Investigate data issues, identify root causes, and improve data quality processes. - Partner with engineering teams to strengthen data reliability and governance. - Partner Across Teams: - Work closely with Product, Engineering, Policy, Operations, and Data teams to build trusted measurement frameworks. - Help create consistent and scalable approaches to transparency reporting and observability. - Explore AI-powered solutions for monitoring model performance and understanding their impact on platform safety. - Drive Business Impact: - Turn complex data into clear insights that support strategic decisions. - Identify emerging risks and opportunities through data analysis. - Contribute to the long-term roadmap for Trust & Safety observability and measurement.

Minimum Qualification(s): - 5+ years of experience in Data Science, Data Analytics, Data Engineering, or a related quantitative field. - Strong SQL skills and experience working with large-scale data platforms (e.g. Hive, Spark). - Proficiency in Python or R. - Experience building data quality monitoring, reporting, or observability solutions. - Experience designing metrics and developing dashboards or reporting tools. - Strong analytical and problem-solving skills with the ability to communicate technical concepts clearly. - Bachelor's degree or above in a quantitative discipline such as Statistics, Computer Science, Mathematics, Engineering, or Economics.

Preferred Qualification(s): - Experience in Trust & Safety, content moderation, risk management, or regulatory reporting. - Experience building end-to-end monitoring or observability platforms. - Familiarity with transparency reporting requirements such as DSA or other regulatory frameworks. - Experience with anomaly detection, experimentation, causal inference, or time-series analysis. - Experience driving data quality initiatives at scale. - Experience working with global cross-functional teams. - Passion for using data to improve online safety.