Growth Measurement & Experimentation Manager

We are looking for a Measurement & Experimentation Manager to own the causal understanding of growth and capital allocation across our global business. This is not a reporting role, it is a decision-making role at the core of the growth engine. You will operate at the intersection of Marketing, Data Science, and Product, building the systems that determine where and how we invest marketing budget. Your mission is to move the organization from correlation (last-click) to causation (incrementality). You will act as a product owner of measurement, defining the roadmap, building experimentation frameworks, and directly influencing executive-level decisions.

 

Own the measurement product & roadmap

• Define and evolve the company-wide measurement strategy (MMM, incrementality, attribution, pLTV bidding)
• Treat measurement as a product, with clear roadmap, adoption, and business impact
• Establish a single source of truth for marketing effectiveness
• Operates as a senior lead who works independently to link complex technical outputs (MMM, pLTV, incrementality) with core business goals

Build a causal experimentation engine

• Design and scale incrementality testing (GeoLift, holdouts, synthetic controls)
• Create a unified experimentation framework across channels and markets
• Ensure all major investment decisions are backed by statistically sound evidence

Drive capital allocation decisions

• Owns the transition from correlation to causation by designing incrementality frameworks that directly drive executive-level capital allocation and marginal ROI decisions.
• Translate complex outputs into clear, actionable investment recommendations
• Partner with Growth leadership to optimize marginal ROI and payback curves
• Actively challenge channel and market decisions with data-backed POVs

Enable cross-channel and creative learning

• Build structured testing frameworks for creatives, formats, and bidding strategies
• Turn experimentation into repeatable learning systems, not one-off tests

Collaborate with Data & Engineering

• Partner with Data Science on MMM, LTV modeling, and causal inference
• Improve signal quality (tracking, attribution inputs, conversion value signals)

 

• Has strong foundation in causal inference, experimentation, or econometrics
• Has experience with incrementality testing and advanced measurement frameworks
• Communicates complex technical concepts efficiently to non-technical teams, gaining their confidence
• Can proactively mitigate conflicts when data challenges existing channel performance
• Able to operate as a product owner, not just an analyst
• Has proven ability to influence budget allocation and strategic decisions
• Has strong collaboration skills with Data Science and Enginee