Director Applied AI for Marketing and Commerce

Over de vacature

Overview

In this role you will lead measurement-driven marketing insights that justify budget decisions and optimize performance in production. You will work closely with client CMOs and cross-functional teams to apply MMM, incrementality, and attribution at scale, while shaping how synthetic assets and AI-enabled studios drive business outcomes. You own the methodology in client environments, ensuring rigorous, production-ready solutions. This is a hands-on, advisory, and impact-focused position that blends data science with strategic storytelling.

Arbeidsvoorwaarden / Benefits

• competitive salary
• phone & travel reimbursements
• remote work allowance
• hybrid work environment
• extensive lunch program
• weekly massage sessions

Verantwoordelijkheden

• Lead Marketing Mix Modelling, incrementality testing, geo-lift and attribution to inform budget decisions
• Develop and productionize models in clients' cloud environments; ensure end-to-end operationalization
• Present methods and findings to CMOs; own recommendations and influence client decisions
• Contribute to the design and improvement of measurement stacks and productization of measurement capabilities
• Collaborate with scientists, engineers, creatives and strategists to refine models and outputs
• Engage directly in qualification and solution design, not just post-sale handoffs
• Partner with frontier labs and external AI vendors to explore and apply cutting-edge approaches
• Provide production-level oversight and debugging when issues arise in live deployments
• Shape offerings and help decide what to productise and take to market
• You will work with privacy-conscious, live-experiment data and identify robust identification strategies

Belangrijkste vereisten

• Deep marketing measurement expertise (MMM, incrementality, attribution) with hands-on model building and deployment experience

• Genuine marketing fluency across retail media, paid social, and brand-building dynamics

• Serious data science background with causal inference, Bayesian methods, forecasting, and optimization; coding ability

• CMO-grade communication to explain complex methods and actionable recommendations

• Production instincts: MLOps, cloud deployment, production-ready deliverables

• Presence in client-facing contexts from qualification to design and defense of solutions

• AI-native working style; daily use of AI tools and willingness to adapt workflows

• Exposure to measurement in dynamic, ambiguous environments (proven track record with budgets impact)

• Masters/PhD or strong quantitative body of work is advantageous (optional)

• Clear communication

• Problem ownership

• Collaborative mindset

• Causal inference

• Bayesian methods

• MMM, incrementality, attribution

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