Responsibilities

• Channel Performance Measurement & Analytics
• - Measure and report on performance across email, direct mail, and digital — defining the right metrics, building reporting, and surfacing what is working and what is not
• - Own digital analytics end to end, including event tracking and tagging strategy, and partner with engineering to ensure data is captured accurately across web and app properties
• - Build and maintain attribution and marketing mix models to quantify channel contribution and guide budget allocation across the marketing portfolio
• - Analyze paid channel performance — spend efficiency, ROAS, and incrementality — and translate findings into clear optimization recommendations
• Data Science & Advanced Modeling
• - Own marketing mix modeling (MMM) end to end — building, validating, and refreshing models that quantify channel contribution, diminishing returns, and saturation to guide budget allocation
• - Develop propensity models to predict member behavior — conversion, churn, and engagement — and operationalize scores to drive targeting, segmentation, and lifecycle marketing
• - Apply Bayesian network analysis and related probabilistic methods to model relationships between marketing drivers and outcomes, quantify uncertainty, and support causal and incrementality analysis
• - Partner with data engineering to productionize models, monitor performance over time, and ensure outputs are reliable, explainable, and decision-ready for leadership

Requirements

• 10+ years in marketing analytics, data analytics, data science, or a closely related field, with the experience and technical expertise to function successfully and independently in this role
• Strong SQL skills, including the ability to write complex queries against large datasets
• Hands-on experience with Snowflake and dbt (or comparable cloud data warehouse and transformation tooling)
• Proven experience measuring email, direct mail, and digital marketing performance
• Working knowledge of attribution, marketing mix modeling, and paid channel analysis
• Hands-on experience building data science models — including marketing mix modeling, propensity modeling, and Bayesian network analysis — and applying them to real marketing decisions
• Solid understanding of A/B testing — experiment design, sample sizing, significance, and interpretation
• Practical understanding of analytics tagging and tracking and of how APIs work for pulling and integrating data
• Familiarity with HTML, CSS, and JavaScript — enough to understand tracking implementation, debug data collection, and work alongside engineers
• Demonstrated use of AI tools such as Claude to support analysis, reporting, and workflow automation

Preferred

• Agency experience
• E-commerce experience
• Experience with a marketing or product analytics platform (e.g., GA4, Amplitude, Adobe Analytics)
• Familiarity with incrementally measurement and experimentation platforms
• Experience with Python or R for analysis

Benefits

• A competitive compensation package in line with leading technology companies
• A remote and accomplished global team
• Opportunity for equity participation
• Unlimited vacation with manager approval
• 16 weeks of 100% paid parental leave for delivering parents; 8 weeks of 100% paid parental leave for non-delivering parents
• 100% Employer sponsored healthcare, dental, and vision for you, and 80% coverage for your family; Health Savings Account and Flexible Spending Account options
• 401k retirement savings plan