Data Scientist, Transparency & Observability - Trust and Safety

Description

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.

Requirements

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.