Data Science Lead, Measurement Science

About the Team:

The TikTok Measurement-Research Data Science Team drives advertisers' behavioral change on TikTok through rigorous data science research in quantitative marketing, helping stakeholders make decisions using scientific approaches. The team conducts empirical and theoretical research, uses object-oriented programming for pipeline prototyping, and offers educational opportunities to the broader TikTok community. They are a research-focused team that values ideas and works closely with others through constant communication and brainstorming. The team is hosted within the larger Measurement - Research team that develops strategic knowledge across audience, full funnel, commerce, creative, search, and moments programs



About the Role:

This role is not merely an application of Data Science; it is the leadership of Measurement Science as a distinct, specialized discipline. Your team will function as an internal research group responsible for the fundamental quantitative understanding of our business.



Responsibilities:

Driving Scientific Inquiry and Revenue:

- Define Foundational Measurement: Lead the research and implementation of Post-campaign measurement —including econometrics, causal modeling, and quasi-experimentation—to move beyond correlation and accurately quantify the incremental revenue (Lift) generated by all of TikTok's advertising products.

- Pioneer Research Agenda: Own the research roadmap for advanced measurement topics that directly underpin monetization: Marketing Mix Modeling (MMM), incrementality studies, creative measurement, and unified full-funnel measurement across online and offline channels.

- Advance Causal Inference: Apply and innovate within the domain of causal inference to address complex, non-experimental questions related to auction dynamics, content algorithm influence, and the long-term Customer Lifetime Value (LTV) impact of ad campaigns.

- Code and Collaborate: Serve as the technical authority and hands-on coder for the team, architecting and prototyping scalable models in languages like Python. Ensure scientific methods translate into robust, production-ready tools for the Monetization organization.

- Translate and Influence: Translate complex statistical outputs and academic findings into clear, pragmatic recommendations for executive leadership, directly shaping Monetization strategy and ad product development.