About the team

You'll be leading Stripe's Marketing Data team. This team works with Stripe Marketing to support Stripe's growth by building awareness, improving brand perception, scaling self-serve experiences, expanding the sales pipeline across all segments, and driving multi-product adoption. You will work closely with Marketing leadership to drive data-informed strategies that will accelerate Stripe's growth. The team works across a wide range of marketing channels and aims to reach a diverse audience of customers including startups, small businesses, major enterprises, and consumers.
What you'll do

Stripe's Marketing Data team helps Marketing make informed decisions about where and how to invest for growth. As the team's leader, you'll set the direction for data science, analytics, and modeling across Stripe's marketing efforts. You'll partner with Marketing leadership and teams across Sales, Growth, Product, Finance, and Engineering to connect data, measurement, and business strategy.

You'll build and develop an organization that turns complex questions into practical decisions. Your team will strengthen how Stripe measures incremental impact, identifies growth opportunities, and uses artificial intelligence in marketing, while creating reliable data foundations that teams can use to make consistent decisions.

Data Science at Stripe employs the full toolbox in order to advance our mission of building world-leading financial products and infrastructure, from experiments and causal inference, to working with our partner teams to rigorously define and forecast metrics. If this sounds exciting, we hope you will join us!
Responsibilities

• Set the vision and multi-year roadmap for Marketing Data, aligning the team's priorities with Stripe's broader growth strategy
• Serve as a leader across Marketing and Data Science, helping shape strategy and representing the role of data in key company decisions
• Build a marketing measurement strategy that connects marketing investments to incremental growth, pipeline, revenue, product adoption, and long-term customer value
• Guide investment decisions across channels, audiences, markets, and products, helping leaders understand tradeoffs and allocate resources
• Develop targeting, propensity, and optimization models that improve how Stripe reaches and engages prospective and existing users
• Partner with Marketing and Finance leadership on forecasting, goal setting, budget planning, and performance management
• Establish trusted marketing metrics, data sources, and measurement standards that teams can use to make consistent decisions
• Set the direction for how Marketing uses AI to improve decision-making, campaign execution, and team productivity
• Turn complex analysis into clear recommendations, influencing senior leaders and building alignment across functions
• Build and develop a high-performing organization of data scientists, analysts, and managers, with clear standards for quality and impact
• Partner with senior leaders across Sales, Growth, Product, Finance, and Engineering to deliver shared business outcomes

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements

• 15+ years of relevant experience with a bachelor's degree, 12+ years with a master's, or 8+ years with a PhD in a quantitative field
• 5+ years leading data science or analytics teams, including 3+ years managing managers and scaling organizations
• Experience as a senior data leader shaping business strategy and influencing executive decisions
• Deep marketing data science experience, including measurement, experimentation, causal inference, targeting, attribution, or investment optimization
• Ability to set a long-term data strategy and translate it into a focused roadmap with measurable outcomes
• Track record of leading complex, cross-functional data initiatives from ambiguous problem definition through adoption
• Strong statistical foundation, particularly in measuring marketing effectiveness and incremental impact
• Working knowledge of SQL and a scientific computing language such as Python or R
• Ability to turn complex analysis into clear, actionable recommendations for senior leaders
• Proven ability to build alignment across Marketing, Finance, Product, Sales, and Engineering
• Demonstrated success recruiting and developing senior data scientists, analysts, and managers