Global E-commerce Data Science PhD Intern – Global E-commerce

Job Description

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

The Tone:
This is an internship at TikTok, with a 2026 start. TikTok builds a leading global platform for short-form mobile video and powers an e-commerce platform called TikTok Shop. The Global E-commerce Data Science team builds analytical frameworks and product metrics to drive growth, improve operational efficiency, and optimize user experiences within TikTok Shop. This role matters by contributing to insights from product usage data, informing product improvements, and enabling data-driven decision-making at a global scale.

The TL;DR
• Role: Internship
• Type: Seasonal
• Location: In-person, Los Angeles, CA
• Pay: $52.25 hourly
• Team: Global E‑commerce Data Science team
• Mission: Drive growth, improve operational efficiency, and optimize the buyer, seller, and creator experiences across regions by leveraging analytical frameworks and product metrics.
• Tech Stack: SQL, Python, R

What You’ll Actually Do
• Analysis: Analyze product usage and engagement data (e.g., retention, conversion, feature adoption) to identify trends and actionable insights.
• Experimentation: Support the design and evaluation of A/B tests or feature experiments; compute lift, assess statistical significance, and help interpret outcomes.
• Exploration: Conduct exploratory data analysis using SQL and Python to detect patterns, anomalies, or feature-driven behaviors.
• Reporting: Create dashboards, visualizations, and summary reports to communicate findings to product, engineering, and design teams.
• Collaboration: Collaborate cross-functionally with product managers and engineers to implement metrics and iterate on insights; document analysis and methodologies.

The Must-Haves
• Background: Currently pursuing a PhD in Computer Science, Statistics, Econometrics, Mathematics, or other quantitative disciplines.
• Experience: Practical experience with data querying and scripting languages (e.g., SQL, Python, R) and basic statistical/data analysis tools.
• Skills: Proficient in data analysis tools and languages such as SQL, Python, or R; Familiar with statistical modeling, A/B testing, or experiment design concepts, drawn from coursework, projects, or internships.
• Bonus: Familiarity with machine learning frameworks or predictive modeling; Prior internship or project experience in product analytics, A/B testing, or data science roles; Strong communication, collaboration, and storytelling skills to translate technical findings into product recommendations.