Senior Manager, Marketing Decision Science

This is a high-visibility leadership role at the intersection of marketing, data science, analytics, and strategic investment decisions. You will lead a team of Decision Scientists and Marketing Analysts responsible for measuring and optimizing the impact of paid media, SEO, and retailer marketing. Your work will directly influence marketing budgets, channel strategies, growth initiatives, and long-term customer value. You will partner closely with senior marketing leaders and Finance, representing the analytics function in important business reviews and planning forums. The role combines people leadership, advanced marketing measurement, causal analysis, and hands-on data fluency. It offers the opportunity to shape a unified marketing measurement framework while building a high-performing analytical team in a fast-growing technology environment.

• 8+ years of experience in data science, analytics, or another quantitative discipline, including at least 3 years of direct management experience leading teams of analysts or Decision Scientists.
• Deep expertise in paid marketing measurement, including incrementality testing, Media Mix Modeling, attribution, Lifetime Value-based optimization, and channel-level performance analytics.
• Strong SQL and data fluency, with the ability to work directly with data, validate analytical approaches, and pressure-test team output.
• Demonstrated ability to independently manage senior cross-functional relationships and represent an analytics or data science function in leadership forums without requiring escalation.
• Proven ability to translate complex quantitative analysis into clear investment recommendations and business insights for non-technical stakeholders.
• Experience managing and developing Decision Scientists or Marketing Analysts, with a strong focus on analytical quality, professional growth, and constructive feedback.
• Experience in a consumer-facing marketplace or high-growth technology environment is preferred.
• Familiarity with geo-experimentation, Bayesian methodologies, or causal inference frameworks is a plus.
• Experience with Lifetime Value-based media optimization and marketing budget allocation modeling is preferred.
• Background in building or transforming channel-level reporting and pacing infrastructure is an advantage.
• Strong communication, stakeholder management, prioritization, and people leadership skills.
• Comfortable operating in a fast-paced environment with complex, evolving priorities and a high degree of cross-functional collaboration.