About the Team The Marketing Data Science team, part of Marketing Insights & Analytics, is a critical business partner to Global Brand & Communications and Global Marketing. We bridge technical rigor with business strategy, delivering data science solutions that drive marketing efficiency and impact. About the Role You will join a team that is responsible for marketing revenue modeling, campaign measurement, and deep-dive analyses to uncover market opportunities. We focus on building, expanding, and automating data science capabilities, influencing top-line budget allocation and shaping TikTok’s marketing strategy at scale. 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. - Influence cross-functional stakeholders (marketing, insights, product, engineering), driving alignment on data-driven marketing strategy. - 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.
Minimum Qualifications - 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. - 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. - Proven ability to effectively communicate complex data insights to both technical and non-technical audiences. - Demonstrated ability to lead complex projects, manage stakeholder relationships, and influence decision-making processes without formal authority. Preferred Qualifications - Ph.D. in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, Economics, or a related field. - 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. - Proven ability to work with marketing, product, engineering, and operations teams, translating complex statistical insights into actionable business strategies.
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