Data Engineer, Emerging Product - USDS

About the Team

The Emerging Product Engineering Team is the incubator for TikTok USDS JV's newest ventures in the US market. We are responsible for the end-to-end success of a diverse portfolio applications. We operate with a strong “0→1” mindset, prioritizing agility, rapid iteration, and creative problem-solving to build and scale products.

We are now looking for a Data Scientist who thrives in fast-paced, ambiguous environments and is passionate about building new businesses from the ground up. In this role, you will define measurement frameworks, unlock user insights, and build data-driven foundations that enable our emerging products to launch, localize, and scale successfully in the U.S. Market.

Responsibilities

• Define 0→1 Metrics: Partner closely with Product Managers, Engineers, and growth teams to establish core KPIs, product health metrics, and foundational tracking for early-stage products.
• Unlock User Insights: Analyze early user behavior, engagement funnels, and retention patterns to deliver actionable insights that directly influence product roadmaps and successful U.S. market entry.
• Experimentation & Iteration: Design, execute, and analyze A/B tests or quasi-experiments to validate new features, localization efforts, and growth strategies under rapid iteration cycles.
• Data Infrastructure Collaboration: Work with data engineering teams to design scalable data pipelines, telemetry requirements, and robust dashboards that ensure high data quality and observability.
• Cross-Functional Partnership: Communicate complex data findings clearly to global engineering teams and cross-functional stakeholders (e.g., operations, marketing, and compliance) to align strategic goals.

Minimum Qualifications

• BS / MS in a quantitative field (e.g., Data Science, Statistics, Computer Science, Economics, Mathematics, or related field).
• 3+ years of data science or product analytics experience, delivering hands-on insights for consumer-facing production applications.
• Proficiency in SQL and at least one programming language used for data analysis (e.g., Python or R).
• Solid understanding of statistical concepts, experimental design (A/B testing), and core product metrics (retention, conversion, engagement).

Preferred Qualifications

• Experience working in an incubator, startup, or "0 to 1" product environment.
• Strong business acumen with a proven track record of turning ambiguous, messy data into structured, actionable product recommendations.
• Familiarity with data visualization tools (e.g., Tableau, Looker) and distributed data processing frameworks (e.g., Hive, Spark).