Data Science intern (TikTok-Product-Data Science-UG Mid-Platform-US) – 2025 Start (BS/MS)
About this internship
TikTok is hiring a Data Science intern for its Product Data Science team in San Jose, CA, with an on-site work model. This 2025 start role is designed for BS/MS students in quantitative fields such as mathematics, statistics, economics, or computer science, and pays $35/hr. You’ll likely work with data to support business analysis and turn findings into actionable insights, with ads or marketing industry exposure considered a plus. Candidates should be able to intern at least 3 days per week for a minimum of 3 months.
Qualifications
Required
- Education Background: Academic background in quantitative fields such as mathematics, statistics, economics, or computer science.
- Analytical Skills: Previous internship or project experience in business analysis or data-related roles, with the ability to analyze data and generate actionable insights. Experience in the ads or marketing industry is a plus.
- Availability: Able to intern at least 3 days per week for a minimum of 3 months.
Nice to have
- Coursework or projects involving statistics, probability, or applied machine learning in a business context
- Experience translating analytical results into clear recommendations for non-technical partners
- Familiarity with common marketing or ads concepts (e.g., attribution, conversion, funnel metrics)
- Demonstrated ability to scope an ambiguous problem into measurable questions and success metrics
- Strong attention to detail when validating data and explaining assumptions and limitations
How to stand out (TUN tip)
When you apply, highlight 1–2 projects or internships where you analyzed real data and produced a concrete decision or recommendation, including the metric you moved or the insight you uncovered. If you have any ads or marketing-related exposure, briefly connect it to how you approached measurement and impact. Also confirm your availability (at least 3 days/week for 3+ months) and your on-site location preference for San Jose.