Responsibilities

• Partner with large global advertisers and agencies to develop measurement strategies and learning agendas that quantify advertising effectiveness and inform business and investment decisions.
• Translate business questions into measurable hypotheses and design appropriate experimental or analytical approaches, including defining study populations, treatment and control structures, outcome metrics, measurement windows, and data requirements.
• Apply and interpret statistical and causal measurement methods across solutions such as Brand Lift Studies, Conversion Lift Studies, incrementality experiments, geo-based measurement, attribution / MTA, Marketing Mix Modeling, Store Visit measurement, and other relevant measurement approaches.
• Analyze and interpret quantitative results using inferential statistical methods, including lift estimation, statistical significance, confidence intervals, regression-based analysis, and other causal or observational techniques; assess data quality, assumptions, bias, and methodological limitations.
• Use analytical tools such as SQL, R, and TikTok proprietary measurement systems, or partner with Measurement Analysts and Data Science teams on analysis, while owning the methodological interpretation and translation of findings into actionable client recommendations.
• Partner with Sales, Product Marketing, Measurement Product, Data Science, and other cross-functional teams to improve measurement methodologies, scale best practices, and ensure client and agency feedback informs product and measurement development.

Requirements

• 5+ years of experience in digital advertising, marketing measurement, marketing science, analytics, measurement suppliers, or other relevant quantitative functions.
• A track record of inferential problem solving through experimental or study design, statistical analysis, and other quantitative analytical methods.
• Demonstrated ability to translate business questions into measurement plans, select appropriate methodologies, and interpret quantitative results, assumptions, uncertainty, and limitations.
• Exceptional time-management and goal-oriented task management skills.
• A track record of driving client decisions through clear communication, quantitative evidence, and cross-functional collaboration.
• Ability to work effectively and consistently in a fast-paced environment with global stakeholders.

Preferred

• Relevant bachelor's degree in a quantitative field such as mathematics, statistics, economics, engineering, operations research, computer science, data science, or a related discipline; graduate degree in a quantitative field preferred.
• Experience in the FinServ/Health/Auto/Telco industry or supporting FinServ/Health/Auto/Telco advertisers and agencies preferred; experience working across other industry verticals and adapting measurement approaches to different business models, customer journeys, and conversion cycles is also beneficial.
• Experience with advertising agencies, advertising platforms, or other complex marketing data environments.
• Experience using SQL and/or R for quantitative analysis and working with large-scale advertising or experimentation datasets.
• Experience with advertising measurement methodologies such as lift experiments, causal inference, geo-based measurement, attribution / MTA, or Marketing Mix Modeling.
• Familiarity with privacy-first measurement systems and methodologies.

Benefits

• Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).