TikTok is looking to solve marketing revenue modeling, campaign measurement, and deep-dive analyses to uncover market opportunities. The role aims to build, expand, and automate data science capabilities to influence top-line budget allocation and shape TikTok's marketing strategy at scale.
Requirements
- Strong programming skills in SQL and either Python or R, with experience in data querying, manipulation, and advanced statistical analysis.
- Experience with experimental design methodologies, including A/B testing and causal inference techniques.
- Strong background in Marketing Mix Modeling (MMM), causal inference (e.g., DiD, Synthetic Control, Instrumental Variables), and experimental design beyond standard A/B testing (e.g., CUPED, meta-analysis, Bayesian methods).
- Experience designing and analyzing geo-testing, creative testing, and incrementality experiments to measure marketing effectiveness and inform budget allocation.
- Advance causal inference methodologies in marketing measurement, including behavior and conversion lift studies (A/B testing with CUPED & DiD).
- Conduct meta-analyses to assess holistic A/B testing impact and drive strategic recommendations.
- Enhance automation & reporting, maintaining data pipelines, dashboards, and self-serve tools to streamline marketing analytics.
Responsibilities
- Lead Marketing Mix Modeling (MMM) execution and adoption, ensuring methodological rigor and translating outputs into actionable marketing insights.
- Communicate the methodology with data science teams across different orgs, highlighting model advantages and limitations.
- Advocate for MMM’s role in budget allocation and campaign optimization.
- Ensure methodological rigor in vendor-led research, reviewing experimental design, statistical approaches, and validity of findings.
- Expand marketing data science capabilities, including: Incrementality Measurement: Develop and refine methodologies to assess marketing impact beyond standard A/B testing.
- Budget Optimization: Leverage MMM and experiment-based insights to inform media investment and marketing spend efficiency.
- Forecasting & Market Dynamics: Build predictive models for scenario planning and strategic marketing investment decisions.
Other
- Influence cross-functional stakeholders (marketing, insights, product, engineering), driving alignment on data-driven marketing strategy.
- Demonstrated ability to lead complex projects, manage stakeholder relationships, and influence decision-making processes without formal authority.
- Proven ability to work with marketing, product, engineering, and operations teams, translating complex statistical insights into actionable business strategies.
- Master's degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, Economics, or a related field.
- 5+ years in data science roles within business strategy, marketing, finance, engineering, or analytics organizations.
