Responsibilities

• Lead incrementality studies end to end, from defining the business question and assessing feasibility through test design, execution, analysis, and final recommendation
• Serve as a testing and measurement subject matter expert, advising Product Marketing, Finance, Data Science, and activation partners on hypotheses, KPI selection, sample requirements, test design, and interpretation
• Design and analyze experiments using methods such as randomized A/B tests, geo experiments, matched-market studies, synthetic controls, and Difference-in-differences
• Geo-Based Measurement: Develop and analyze geo-experiments to measure marketing incrementality and validate MMM outputs
• Communicate complex analytical concepts clearly and concisely to both technical and non-technical audiences, including senior business stakeholders
• Prioritize, project-manage, and drive multiple analytics and testing workstreams forward under tight timelines, while proactively communicating progress, risks, tradeoffs, and decisions needed
• Manage a portfolio of measurement projects independently, ensuring strong stakeholder alignment, clear documentation, and high-quality execution from intake through final recommendation
• Develop and improve scalable processes, data standards, dashboards, automation tools, and analytical techniques that increase marketing effectiveness, measurement quality, and team efficiency
• Stay current on the digital advertising and measurement ecosystem and creatively apply measurement solutions in ways that improve advertiser, member, and business outcomes

Requirements

• Bachelor’s degree in statistics, economics, applied mathematics, business analytics etc.
• 5+ years of relevant industry or academic experience in data science, marketing science, experimentation, causal inference, econometrics, or a related analytical field
• Working knowledge of causal inference methods, including geo-experimentation and observational approaches
• Experience designing and analyzing experiments, such as A/B tests, geo experiments, or matched-market studies
• Experience in SQL
• Background in at least one programming language (e.g., R, Python, Scala)
• Experience in applied statistics and statistical modeling in at least one statistical software package
• Ability to communicate complex concepts clearly to stakeholders at varying technical levels

Preferred

• MS or PhD in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
• Hands-on experience with geo-based experimentation, synthetic-control methods, difference-in-differences, Bayesian structural time-series models, or other approaches used to measure marketing incrementality
• Experience with Marketing Mix Modeling, modeled attribution, conversion lift, brand lift, ROI analysis, or the validation and calibration of marketing measurement models
• Experience with manipulating massive-scale structured and unstructured data
• Familiarity with Bayesian modeling and its applications in marketing
• Familiarity with AI-assisted coding and analytical tools used to accelerate prototyping, analysis, documentation, or workflow automation
• Passion for marketing and consumer science, with a desire to stay informed about the latest advances in the field