Responsibilities

About Data Cycling Center (DCC) AI is the new electricity and data is the energy for AI. Our core belief is that unstructured data contains the untapped wisdom of humanity — and by building the best AI-ready data infrastructure, we enable more meaningful, responsible, and creative uses of AI. Data Cycling Center (DCC) is a Data Science team that is responsible for building the mid-platform data layer that powers AI development across all business lines of TikTok, including e-commerce, advertising, livestreaming, and emerging technologies. Our initiatives include: - Scaled human-in-the-loop (HITL) data processing (including capability, methodology, E2E process, platform), delivering the most cost-effective results at benchmark quality levels that outperform leading tech peers. - Built a highly automated end-to-end data pipeline for AI-generated content (AIGC) that supports strong model performance with minimal resource input. - Develop a comprehensive content understanding and insight generation system, setting new benchmarks for marketing intelligence in the online ads ecosystem. DCC aims to be the number 1 data service provider in the AI era. Our mission is to build the most effective (lossless and affordable) content understanding capabilities to fully satisfy AI needs of TikTok and to help the industry push the limit. About the Team The Data Acquisition team is where raw human complexity meets machine reasoning. We're building systems that translate the messiness of human behavior — language, perception, decision-making — into structured, learnable intelligence for frontier AI models. Our job isn't to clean up data. It's to understand it — in all its ambiguity, context, and contradiction — and make it usable for models pushing the limits of what AI can do. We work on: - Building novel data science solutions that evolve with human input - Designing tooling that captures nuance across text, audio, video, and human feedback - Creating robust signals from subjective and messy real-world data - Scaling dynamic data operations to support multi-modal model training About the Role We're looking for a highly capable Data Scientist/Data Solutions Manager to build the next generation of data solutions in support of industry leading products and services that TikTok provides. You will be assessing business needs, innovating across your given resources, and navigating across both business and technical XFN stakeholder teams. You will design solutions to build data labeling at scale, using state-of-the-art algorithms and recognition models to improve datasets and optimize the requirement handling mechanism and process. You will also drive analytics and insights to aid business decisions and the quantification impact of initiatives through scientific approaches (like experimental designs). Responsibilities 1. Work closely with stakeholders to capture requirements for data labeling projects; 2. Track the progress of data labeling projects and manage resources to ensure timely completion; 3. Develop strong relationships with XFN partner teams to deliver efficient data solutions that support revenue generation and cost savings; 4. Translating complex business requirements into technical product solutions; 5. Enhance on the service and quality of labelled data delivery; 6. Innovate across multiple different data product types to reduce cost and increase impact; 7. Utilize experience to recommend the right machine learning techniques to the appropriate business use-cases; 8. Experience the entire model pipeline from data gathering to model delivery and maintenance. What you will need 1. Solid foundations of statistics and data science/analytics projects management is preferred; 2. Outstanding skills of communication, collaboration, project management, problem solving, and an excellent team player; 4. Strong interest in process optimisation and improvement; 5. Highly conscientious with good attention to detail; 6. Experience in artificial intelligence, computer vision, and machine learning techniques and other fields are highly preferred.

Qualifications

Minimum Qualifications 1. Bachelor's degree in Computer Science, Engineering or equivalent practical experience; 2. Experience with writing and optimizing SQL, and with one general purpose programming language (e.g., Java, C/C++, Python); 3. Experience in data analytics and data visualization. 4. Excellent proficiency in both written and spoken English Preferred Qualifications 1. Experience in client facing roles/consulting preferred. 2. Experience collaborating with cross-functional and global teams.

Job Information