Director, Marketing & Data Science

Director, Marketing & Data Science

This role is to be based near one of our offices in Los Angeles, New York City or Austin. (Hybrid)

We drive intelligent growth for ambitious businesses and leading brands. Customer understanding is more potent and drives greater value when insights go to work directly within marketing and experience priorities. To give our clients that advantage, we put an insights-driven operating system at the core of our design, go-to-market, and digital experience solutions.

Material clients make smarter growth choices because they can see clearly how and when to take the shots that count. Together, we connect consumer intelligence with customer demand generation to build lasting, profitable relationships.

Material is seeking a Director for the Marketing & Data Science team who is passionate about using data science to solve complex marketing and customer problems. This role sits at the intersection of advanced analytics, market research, customer data, and business strategy. You will lead engagements that bring together consumer surveys, first-party CRM and CDP data, transactional data, and digital behavior to help clients make better decisions and drive measurable growth.

You lead by doing: shaping the analytical approach, guiding your team through execution, and translating model outputs into clear stories for senior, non-technical audiences. You are curious about human behavior, rigorous about methodology, and practical about how AI can accelerate the work without replacing the judgment.

Apply AI and machine learning — including LLMs and generative techniques — to accelerate segmentation, synthetic data generation, qualitative-to-quantitative synthesis, and automated insight generation. Design and execute behavioral analytics engagements: clickstream analysis, passive behavioral data, digital journey mapping, engagement modeling, propensity and churn prediction, and customer lifetime value. Integrate behavioral signals — from CRM, CDP, digital, transactional, and survey sources — into unified analytical frameworks that reflect how customers actually make decisions.

Lead technical execution in Python or R across the full modeling lifecycle: feature engineering, model selection, validation, interpretation, and deployment planning. Stay current on advances in AI, machine learning, and behavioral science — identifying what's practically useful for clients versus what's hype.

Own the analytical workstream end-to-end: converting business questions into clear analytic plans, timelines, and decision-ready outputs. Deliver executive-ready narratives that connect behavioral findings to marketing actions and measurable business outcomes. Serve as a trusted subject matter expert — explaining complex methods, defending recommendations, and redirecting analyses that won't answer the underlying question. Partner across research, strategy, technology, and data engineering to build solutions that can be activated in client environments.

Support business development by shaping analytical approaches, scoping work, and contributing to proposals.

Lead and mentor a pod of analysts and data scientists — providing direction, code review, and opportunities for technical and professional growth. Review analytical plans, model outputs, and client deliverables; catch risks early and help teams troubleshoot. Contribute to practice growth through knowledge sharing, capability development, and methodological innovation.

7–10+ years in data science, marketing analytics, or quantitative research — agency, consulting, or in-house. Solid…