Ecommerce Data Scientist: Growth Analytics & ML

TikTok Inc.; San Jose (CA); On-site; USD 144,000 - 329,000; Full time

Job summary

TikTok USDS Joint Venture LLC in the United States is seeking a data scientist to turn data into actionable product insights for its e‑commerce initiatives. You will work with large datasets, build models, and communicate findings to stakeholders to influence product strategy.

The role emphasizes collaboration with PM/Ops/R&D, dashboard development, and ML experimentation to optimize user engagement and revenue in a fast‑growing tech environment.

Qualifications

• Master’s degree or above in mathematics, statistics, or computer science.
• Proficient in SQL, Tableau and familiar with Python or R for modeling.
• 3+ years of experience in data science and machine learning.
• Effective communication of data analyses to stakeholders to drive business impact.

Responsibilities

• Work with large and complex datasets to solve problems using analytics and statistics.
• Apply quantitative analysis, data mining, and experiments to inform e‑commerce strategies.
• Define success metrics, forecast outcomes, and monitor product KPIs.
• Identify opportunities to improve product and drive roadmap through insights.
• Develop data pipelines and dashboards to enhance data infrastructure.
• Develop ML models to identify creators and measure user lifetime value (LTV).
• Cooperate with PM/Ops/R&D and other cross-functional teams to inform, influence, and execute product strategy and investment decisions.

Skills

SQL

Tableau

Python or R

Data storytelling

Experimentation & modeling

Education

Master's degree in mathematics, statistics, or computer science

Job description

TikTok USDS Joint Venture LLC in the United States is seeking a data scientist to turn data into actionable product insights for its e‑commerce initiatives. You will work with large datasets, build models, and communicate findings to stakeholders to influence product strategy.

The role emphasizes collaboration with PM/Ops/R&D, dashboard development, and ML experimentation to optimize user engagement and revenue in a fast‑growing tech environment.