Applied Data Scientist

Responsibilities

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:
We are looking for experienced data scientists to join our team and apply advanced analytics and machine learning techniques—including Prompt Engineering (PE), multi-modal large language models (LLMs), computer vision (CV), natural language processing (NLP), and audio signal processing—to optimize intelligent labeling workflows and data products within TikTok's ecosystem. Your work will help improve user experience, enhance content integrity, and support data-driven strategic decision-making. You will collaborate closely with cross-functional teams across product, operations, and algorithms to build scalable, end-to-end Prompt Engineering and LLM workflows for intelligent content moderation and labeling applications.

Key Responsibilities

• Collaborate with cross-functional stakeholders to gather and refine requirements for data labeling projects and identify opportunities for optimization through data-driven solutions.
• Design and manage the full lifecycle of end-to-end data labeling and policy testing workflows — from aligning with business needs to deployment, iteration, and monitoring.
• Establish and maintain a centralized knowledge base for Retrieval-Augmented Generation (RAG) systems, incorporating both structured (e.g., SOPs, guidelines) and unstructured (e.g., annotations, case logs) data to support LLM-based policy QA and labeling efforts.
• Operationalize intelligent labeling pipelines leveraging Prompt Engineering, agent-based workflows, and labeling models to ensure availability of high-quality data for model training and policy evolution.
• Translate complex policy documents into machine- and human-readable formats, support agent and PE strategy development, and evolve nuanced policy edge cases in sync with fast-changing regulatory or platform dynamics.
• Apply multi-modal LLM techniques to extract latent signals from content that inform moderation strategies and highlight policy gaps.
• Lead applied ML and data science research and experimentation to solve business-critical use cases.
• Own the model lifecycle from data sourcing and preprocessing to training, deployment, and post-launch maintenance.

Qualifications Minimum Qualifications:

1. Advanced degree (Master's or Ph.D.) in Statistics, Computer Science, Applied Mathematics, Data Science, or a related quantitative field.
2. Strong theoretical foundation in computer science, machine learning, and statistics, with industry experience in deep learning and at least one of the following: Prompt Engineering, LLMs, CV, NLP, or speech recognition.
3. In-depth experience in unsupervised learning, clustering algorithms, and pattern recognition from unstructured data such as text or video.
4. Strong experience with unsupervised learning, clustering algorithms, and extracting data insights from unstructured video format data, recognizing patterns, and developing models.
5. Experience in data project management, and solid foundations of maths and algorithms.
6. Expertise in SQL, Hive, Presto, or Spark, and experience with large-scale datasets; along with strong proficiency in Python and Deep Learning frameworks such as TensorFlow or PyTorch.
7. Excellent communication and collaboration skills, with the ability to work effectively across global teams and stakeholders.

Preferred Qualifications:

• At least 3 years of experience in software development or model/data pipeline development, with hands-on experience applying LLM technologies (e.g., Test Time Scaling, Chain of Thought, Retrieval-Augmented Generation, Supervised Fine-Tuning) to real-world problems.
• Deep understanding of data pipeline architecture, model development lifecycle, testing, and deployment.
• Practical industry experience in applying prompt engineering and emerging AI techniques to address diverse business needs.
• Demonstrated strong intellectual curiosity, excellent problem-solving skills, and advanced analytical abilities to deconstruct problems, identify root causes, and propose effective solutions.

About TikTok

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day. We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

Trust & Safety

TikTok recognises that keeping our platform safe for the TikTok communities is no ordinary job which can be both rewarding and psychologically demanding and emotionally taxing for some. This is why we are sharing the potential hazards, risks and implications in this unique line of work from the start, so our candidates are well informed before joining.

We are committed to the wellbeing of all our employees and promise to provide comprehensive and evidence-based programs, to promote and support physical and mental wellbeing throughout each employee's journey with us. We believe that wellbeing is a relationship and that everyone has a part to play, so we work in collaboration and consultation with our employees and across our functions in order to ensure a truly person-centred, innovative and integrated approach.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Engineering and Information Technology
• Industries: Technology, Information and Internet

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