Data Science PhD Intern – Global E-commerce

Job Description

Data Scientist Intern (TikTok Shop Business Product DS) – 2026 Start (PhD) | TikTok

The Tone:
This is an internship at TikTok. The company is a global organization known for its leading short-form mobile video platform, which is significantly expanding into e-commerce. This role is crucial for the Global E-commerce Data Science team, which applies rigorous data analysis and scientific methods to enhance user, merchant, and creator experiences and drive business growth worldwide. The intern’s contributions will directly support product iterations, operational efficiency, and the development of foundational data infrastructure for TikTok’s global e-commerce expansion.

The TL;DR
• Role: Internship
• Location: Varies by selected city; potential for Los Angeles
• Pay: $52.25 hourly
• Team: TikTok Global E-commerce Data Science team
• Mission: Drive business growth, enhance operational efficiency, and improve user, merchant, and creator experiences for TikTok’s global e-commerce products through rigorous data analysis and scientific methodologies.
• Tech Stack: SQL, Python, R, Scikit-learn, TensorFlow, PyTorch, Hive, Spark, Hadoop

What You’ll Actually Do
• Analyze Products: Conduct data analysis for TikTok’s global e-commerce products, covering areas such as creators & merchants, content e-commerce, promotion tools, shoptap, and transaction flow.
• Evaluate Optimizations: Design and analyze A/B tests, evaluate product optimizations, analyze campaign performance, monitor key metric fluctuations, and assess client-side version updates.
• Propose Solutions: Analyze country-specific factors influencing product optimization and business growth, and propose actionable product improvement solutions aligned with business direction.
• Implement Strategies: Collaborate closely with product managers, operations, engineering, and algorithm teams to implement data-driven strategies and deliver measurable business impact.
• Build Systems: Build and maintain e-commerce product metric systems, work with data engineering teams to construct foundational data pipelines and visual dashboards, and enable business stakeholders to gain actionable insights.

The Must-Haves
• Background: Currently pursuing a PhD in Computer Science, Statistics, Econometrics, Mathematics, or other quantitative disciplines.
• Experience: Hands-on experience in A/B testing, regression analysis, and causal inference.
• Skills: Proficient in SQL, Python, or R; strong data visualization skills; clear communication of analytical insights; results-driven and a strong team player.
• Bonus: Experience in cross-border or international e-commerce data analysis or modeling; familiarity with machine learning frameworks or predictive modeling such as Scikit-learn, TensorFlow, or PyTorch; experience with big data technologies like Hive, Spark, or Hadoop; strong cross-functional communication skills.