Data Cycling Center (DCC) is a Data Science team that develops AI-driven content (unstructured data) understanding capabilities, identifies business opportunities from the understanding, and builds products and solutions to capture those opportunities.

Our mission is to simplify the acquisition and utilization of unstructured/unlabeled data. The team act as the data modeling factory, using and analyzing mass data and finding useful insights for business growth.

About the role
As an Applied Al Data Scientist at the Applied AI team, you'll work at the intersection of data science, algorithm innovation, and content ecosystem research. You will collaborate closely with product and algorithm teams to identify actionable insights and build scalable solutions that improve user experience, strengthen content integrity, and support strategic decision-making.

Key Responsibilities:
• Apply data science methods and statistical theory to analyze TikTok's content ecosystem and recommend strategies for improvement.
• Design and define core KPI metrics that measure the health, stability, and fairness of content systems; evaluate trade-offs across different strategies or product interventions.
• Use statistical sampling methods to determine appropriate sample sizes and ensure core metric robustness.
• Build frameworks to assess multi-business content flows, balancing risks from negative content while promoting positive content signals.
• Conduct quantitative research using causal inference, statistical modeling, and experimentation to detect risks and opportunities in the content ecosystem and propose strategic improvement plans supported by unbiased data-driven indicators.