Tik Tok
Data Scientist (Statistical Research), Marketing Insights and Analytics
Tik Tok, Los Angeles, California, United States, 90079
Data Scientist (Statistical Research), Marketing Insights and Analytics
Responsibilities About the Team The Marketing Data Science team, part of Marketing Insights & Analytics, is a key partner to Global Brand & Communications and Global Marketing. We combine technical expertise with business strategy to deliver data science solutions that enhance marketing efficiency and impact. About the Role You will be part of a team responsible for marketing revenue modeling, campaign measurement, and deep-dive analyses to identify market opportunities. Our focus is on building, expanding, and automating data science capabilities to influence budget allocation and shape TikToks marketing strategy at scale. Responsibilities Lead Marketing Mix Modeling (MMM) execution and adoption, ensuring methodological rigor and translating outputs into actionable insights. Communicate methodologies across data science teams, highlighting model strengths and limitations. Advocate for MMMs role in budget decisions and campaign optimization. Review vendor-led research for methodological rigor, experimental design, and validity of findings. Expand marketing data science capabilities, including: Incrementality Measurement: Develop methodologies to assess marketing impact beyond A/B testing. Budget Optimization: Use MMM and experimental insights to guide media investment and marketing spend. Forecasting & Market Dynamics: Build predictive models for scenario planning and strategic investments. Influence cross-functional stakeholders to align on data-driven marketing strategies. Advance causal inference methods in marketing measurement, including behavior and conversion lift studies (A/B testing with CUPED & DiD). Conduct meta-analyses to evaluate holistic A/B testing impacts and inform strategies. Improve automation and reporting by maintaining data pipelines, dashboards, and self-serve tools to streamline analytics. Qualifications Minimum Qualifications Master's degree in Statistics, Mathematics, Computer Science, Engineering, Economics, or related field. 5+ years in data science roles within business strategy, marketing, finance, engineering, or analytics. Strong SQL and Python or R skills for data querying, manipulation, and advanced analysis. Experience with experimental design, A/B testing, and causal inference techniques. Ability to communicate complex insights to diverse audiences. Proven project leadership and stakeholder management skills. Preferred Qualifications Ph.D. in a quantitative discipline. Expertise in Marketing Mix Modeling, causal inference (DiD, Synthetic Control, IV), and advanced experimental design (CUPED, meta-analysis, Bayesian methods). Experience with geo-testing, creative testing, and incrementality experiments. Ability to collaborate across marketing, product, engineering, and operations teams to translate statistical insights into business strategies.
#J-18808-Ljbffr
Responsibilities About the Team The Marketing Data Science team, part of Marketing Insights & Analytics, is a key partner to Global Brand & Communications and Global Marketing. We combine technical expertise with business strategy to deliver data science solutions that enhance marketing efficiency and impact. About the Role You will be part of a team responsible for marketing revenue modeling, campaign measurement, and deep-dive analyses to identify market opportunities. Our focus is on building, expanding, and automating data science capabilities to influence budget allocation and shape TikToks marketing strategy at scale. Responsibilities Lead Marketing Mix Modeling (MMM) execution and adoption, ensuring methodological rigor and translating outputs into actionable insights. Communicate methodologies across data science teams, highlighting model strengths and limitations. Advocate for MMMs role in budget decisions and campaign optimization. Review vendor-led research for methodological rigor, experimental design, and validity of findings. Expand marketing data science capabilities, including: Incrementality Measurement: Develop methodologies to assess marketing impact beyond A/B testing. Budget Optimization: Use MMM and experimental insights to guide media investment and marketing spend. Forecasting & Market Dynamics: Build predictive models for scenario planning and strategic investments. Influence cross-functional stakeholders to align on data-driven marketing strategies. Advance causal inference methods in marketing measurement, including behavior and conversion lift studies (A/B testing with CUPED & DiD). Conduct meta-analyses to evaluate holistic A/B testing impacts and inform strategies. Improve automation and reporting by maintaining data pipelines, dashboards, and self-serve tools to streamline analytics. Qualifications Minimum Qualifications Master's degree in Statistics, Mathematics, Computer Science, Engineering, Economics, or related field. 5+ years in data science roles within business strategy, marketing, finance, engineering, or analytics. Strong SQL and Python or R skills for data querying, manipulation, and advanced analysis. Experience with experimental design, A/B testing, and causal inference techniques. Ability to communicate complex insights to diverse audiences. Proven project leadership and stakeholder management skills. Preferred Qualifications Ph.D. in a quantitative discipline. Expertise in Marketing Mix Modeling, causal inference (DiD, Synthetic Control, IV), and advanced experimental design (CUPED, meta-analysis, Bayesian methods). Experience with geo-testing, creative testing, and incrementality experiments. Ability to collaborate across marketing, product, engineering, and operations teams to translate statistical insights into business strategies.
#J-18808-Ljbffr