TikTok Shop - Data Scientist, Global Moderation

Responsibilities

About the Team
E-commerce's Governance and Experience (GNE) is a global team striving to achieve full satisfaction from customers, promoting a sustainable and risk-free sales environment, and providing the perfect purchase experience. Global Moderation is part of the GNE organization. Our mission is to deliver trustworthy and excellent service experiences for every user of TikTok Shop. Global Moderation is looking for a data scientist who is dedicated to data insight and data solutions, helping to ensure a safe and trustworthy marketplace for our buyers, sellers and creators.

Roles & Responsibilities
- Data Infrastructure & Automation: Design, build, and maintain scalable datasets to support advanced modeling and experimentation. Develop automated data pipelines and monitoring systems using Python/SQL, and build interactive dashboards for key stakeholders.
- Modeling & Indicator Systems: Own the end-to-end development of metrics and predictive models for e-commerce moderation. Design and optimize indicator systems across moderation quality, efficiency, and cost. Build statistical and machine learning models to forecast risks, detect anomalies, and evaluate trade-offs.
- Experimentation & Insights: Conduct deep-dive analyses to uncover drivers of business performance and user behavior. Apply statistical tests, A/B experiments, and causal inference techniques to validate hypotheses. Translate findings into actionable strategies to improve moderation operations.
- Collaboration & Impact: Partner closely with cross-functional teams (operations, policy, product, and engineering) to provide decision science support. Deliver compelling insights through data storytelling and tailored recommendations to drive measurable business impact.

Qualifications

Minimum Qualifications
- Bachelor's degree or above in Computer Science, Statistics, Mathematics, Data Science, or other quantitative fields.
- 5+ years of hands-on experience in data science or related roles, with a strong track record of applying statistical and analytical methods to solve real-world business problems.
- Proficiency in SQL and Python for data extraction, transformation, modeling, and automation.
- Solid foundation in statistics, hypothesis testing, and experimental design (e.g., A/B testing, causal inference).
- Experience with BI tools (Tableau, Power BI, Metabase) and ability to create clear, actionable data visualizations.
- Strong communication and structured storytelling skills, with the ability to adapt insights for both technical and non-technical audiences.