What you'll do
You own the Marketing Mix Model (MMM) end to end: you build it out, grow it from the current US model to a global, hierarchical setup and transform it into an automated platform that steers budget allocation. Full ownership, not a supporting role.
- Turn MMM output into decisions: work with performance marketing and finance to embed results in the budget process and guide teams on the strategic implications.
- Steer the test roadmap that feeds the MMM: based on the signals, determine which channels and questions need testing, and design and run incrementality tests (geo experiments and other causal inference methods) to measure incremental ROI.
- Design a unified measurement framework that connects MMM, attribution and incrementality; MMM for major budget decisions, incrementality-adjusted attribution for channel splits.
- Lead company-wide initiatives that extend causal inference beyond marketing to the experimentation platform, and to forecasting and risk work with Finance and Product.
- Build and scale a full-stack self-service platform that lets stakeholders run budget planning and incrementality tests themselves, in close collaboration with engineers and marketing.
- Together with Data Engineering, build scalable pipelines and further develop the ETL as the modeling stack grows (e.g. adoption of Databricks).
What you'll need
- An AI mindset: you use AI to work faster, automate where it makes sense and help stakeholders do the same.
- Hands-on MMM experience: you know that testing multiple approaches is needed before arriving at a robust, defensible model.
- Strong foundation in Bayesian statistics, rigorously applied to MMM and causal inference.
- Experience turning MMM output into action, in language that marketing and finance understand.
- Expertise in experimentation: designing and evaluating incrementality tests and A/B experiments.
- A talent for actionable insights: you design analyses with the decision in mind.
- Strong Python and SQL skills.
- A pragmatic problem-solver who finds the simplest path through complexity, rather than reaching for convoluted models.
- A creative, proactive builder, equally good at finding the right problems as at solving them.
- Advanced written and spoken English.
Nice to have
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