Data Scientist (Statistical Research), Marketing Insights and Analytics

TikTok; Los Angeles (CA); On-site; USD 80,000 - 130,000; Full time

Job summary

An innovative firm is seeking a Data Scientist to join its Marketing Insights and Analytics team. This role involves leading Marketing Mix Modeling and developing methodologies to assess marketing impact. You will influence budget allocation and marketing strategies through advanced data science techniques. The ideal candidate will have strong skills in SQL and Python or R, with a proven track record in data science and project leadership. Join a dynamic team and help shape data-driven marketing strategies that drive significant business impact.

Qualifications

• 5+ years in data science roles in business strategy, marketing, or analytics.
• Strong SQL and Python or R skills for data querying and manipulation.

Responsibilities

• Lead Marketing Mix Modeling (MMM) execution and advocate for its role in budget decisions.
• Develop methodologies for incrementality measurement and budget optimization.

Skills

SQL

Python

R

A/B Testing

Causal Inference

Data Analysis

Project Leadership

Education

Master's degree in Statistics, Mathematics, Computer Science, Engineering, Economics

Ph.D. in a quantitative discipline

Job description

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 TikTok’s 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 MMM’s 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.