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TikTok

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Data Science Manager - USDS

San Jose

Job Description

About the team
The Data Science team of the Tech and Product department at TikTok USDS is responsible for building high-quality and timely data solutions for the business as the single source of truth and for building easy-to-use and scalable data products to support business growth.

In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.

You will have the exciting opportunity to:
- Lead a team of Data Scientists or Data Analysts to execute company level objectives
- Conduct product analytics to provide product recommendations that drive product growth
- Deep dive into data sources, understand their limitations, and communicate complex data insights through exploratory analysis and research to suggest improvement
- Design and monitor core metrics; understand root causes of metric movements
- Design and build advanced analytical solutions and models to deliver superior business outcomes

Minimum Qualifications:
- 5+ years of experience working in a analytical role, including 2+ years as a people manager
- BS/MS in Computer Science, Math, Economics, Statistics, or other science and engineering fields
- Experience with SQL, Python, or R
- Strong communication skills across technical and non-technical audiences
- Self-motivated, detail-oriented, learn autonomously, and highly organized

Preferred Qualifications:
- Previous experience in data science, data analytics, or product analytics at a consumer technology company.
- Experience with streamlining operation workflow with automation and/or AI
- Passion for social technology products and a curiosity to learn & grow with a fast paced company.
- Experience working with international partners in different time zones.

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About the job

Posted on

Oct 10, 2025

Apply before

Nov 9, 2025

Job typeFull-time
CategoryData Science

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