TikTok Ecosystem - Data Science - Singapore

About the team

The Data Science department is responsible for end-to-end data analysis work across various business directions, including indicator definition and monitoring, experimental design and evaluation, problem research, and opportunity mining. It studies various ecological issues and explores the formulation of strategies beneficial to long-term value. It also researches scientific statistical analysis methods to promote the implementation of data products.

Responsibilities

1. Focus on core issues related to the content ecosystem, leveraging data science and statistical theories. Collaborate with team members working on products and strategy algorithms for the international short video content ecosystem to explore opportunities for enhancing user experience from an ecosystem perspective.
2. Conduct data analysis for the negative content risks of Tiktok, explore governance paths, and guide the business to conduct ecosystem governance from four perspectives: issue discovery, metric definition, governance measures, and experience protection.
3. Evaluated the effectiveness of management measures and designed account-level policy mechanisms to enhance compliance.
4. Employ A/B testing, quantitative analysis, statistical modeling, and causal analysis to identify opportunities and risks within the content ecosystem. Develop unbiased metrics and provide actionable recommendations for iterating and optimizing content ecosystem strategies.

Qualifications

1. Bachelor's or Master’s degree in Statistics, Computer Science, Psychology, Data Science, Human-Computer Interaction, or a related field.
2. 3+ years of experience in data science, survey analytics, or user research at scale.
3. Proficiency in SQL and Python; familiarity with survey platforms and internal tool development is a plus.
4. Strong background in survey design, sampling methods, experimental design, and statistical inference.
5. Experience with data visualization tools such as Tableau, Power BI, or similar.

Preferred Qualifications

1. Excellent communication skills and the ability to translate complex findings into business recommendations.
2. Knowledge of data privacy standards and ethical considerations in user data collection.