Data Scientist Graduate (TikTok-Product-Data Science)-2026 Start (PhD)

Team Introduction
TikTok-Data Science team is responsible for all data science and analytics related work, cooperating with all key value chains in TikTok, including User Growth, PGC, Content Ecosystem, Social, Creation, Product Infrastructure, Research and Science etc. The goal of the team is to generate actionable insights from data and help the stakeholders to make the right decisions. Our main tasks include metrics defining, root cause analysis, experimentation methodology, feature/strategy evaluation and exploratory analysis to find more opportunities.

We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at TikTok.
Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.

PhD:
Applications will be reviewed on a rolling basis - we encourage you to apply early.

Successful candidates must be able to commit to an onboarding date by end of year 2026.

Responsibilities
- Define success metrics to measure product growth and identify problems through monitoring or forecasting
- Apply technical expertise with quantitative analysis, experimentation, data mining to develop strategies for product optimizations
- Quantify the impact of strategies through causal inference and generate actionable insights through deep dive analysis
- Partner with Product, Engineering and cross-functional teams to influence and execute product strategy

Minimum Qualifications
- final year PhD or recent PhD graduates in Mathematics, Statistics, Economics, Computer Science, Data Science or relevant technical field, or equivalent practical experience
- Proficient in data querying languages and at least one scripting language (e.g. Python, SQL, R)
- Experience in one or more of the following methods: forecasting, statistical and causal inference, classification methods.
- Strong product sense and structured thinking, and be able to convert the analysis results into business decisions very well

Preferred Qualifications
- Internship experience in data science
- Research experience in data science
- Experience working with cross functional teams

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