Director, Data Science - Marketing

📋 Description

• • As the Director, Data Science - Marketing at A Place for Mom, you will be instrumental in shaping the future of our marketing strategies by owning the critical functions of marketing measurement, attribution frameworks, and the overarching analytics strategy. This pivotal role places you at the nexus of data-driven decision-making, directly influencing major revenue-generating investments.
• • You will lead and mentor a team of talented data analysts, fostering a high-performance analytical culture while remaining deeply hands-on. Your responsibilities will span the entire data lifecycle, from crafting complex SQL queries and designing rigorous experiments to interpreting findings and presenting actionable insights to senior leadership.
• • This is a unique opportunity to establish and own end-to-end marketing measurement capabilities in a domain that presents genuinely challenging and deeply meaningful analytical problems. The senior living sector is characterized by high-consideration purchases, complex emotional landscapes, extended sales cycles, and significant offline conversion signals, making accurate and insightful measurement paramount.
• • You will be embedded within cross-functional teams, collaborating closely with Marketing, Finance, and Operations. Your mandate will include owning complex, end-to-end projects, championing data quality initiatives, and developing robust self-serve tools that empower the entire organization with data literacy and accessibility.
• • We are seeking an individual with a potent blend of strong business acumen and profound technical depth. This leader will proactively identify emerging opportunities, drive the analytical function's evolution, and hold a significant position in strategic marketing investment discussions, enjoying direct visibility with senior executives and the autonomy to build the function according to best practices.
• • Team Leadership and Development:
• • Manage, mentor, and develop a team of data analysts, setting clear priorities, defining performance standards, conducting regular one-on-one meetings, and cultivating a culture of excellence and continuous improvement.
• • Foster a collaborative environment where team members are empowered to grow their skills and contribute meaningfully to the company's objectives.
• • Cross-Functional Partnership and Communication:
• • Serve as the primary analytical liaison for Marketing, Finance, Technology, and Operations teams, ensuring alignment and driving data-informed strategies across the organization.
• • Regularly present key findings, strategic recommendations, and roadmap updates to senior leadership, translating complex data into clear, compelling narratives.
• • Marketing Measurement and Attribution Ownership:
• • Define and execute the comprehensive marketing measurement strategy, encompassing all paid, organic, referral, and direct channels to provide a holistic view of marketing effectiveness.
• • Oversee and manage relationships with measurement vendors, critically evaluating their outputs, identifying any gaps or limitations, and advocating for the company's analytical needs.
• • Develop and maintain a unified, defensible view of channel performance by triangulating insights from Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), and Geo Lift studies, adeptly reconciling potentially conflicting data signals.
• • Experimentation and Testing:
• • Design, implement, and analyze independent Geo Lift and incrementality tests to rigorously assess the true impact of marketing initiatives.
• • Champion a culture of experimentation, encouraging hypothesis-driven testing across all marketing activities to optimize performance and uncover new growth avenues.
• • Reporting, Insights, and Data Enablement:
• • Own the development and maintenance of production-grade Tableau dashboards for critical marketing performance metrics, funnel analytics, and conversion tracking, ensuring data accuracy and accessibility.
• • Move beyond routine reporting by proactively identifying non-obvious insights, pinpointing key conversion levers, and developing a strategic roadmap for future testing and optimization initiatives.
• • Uphold the highest standards of data quality, ensuring data is accurate, accessible, and readily available for analysis across the organization.
• • Drive the democratization of data by building intuitive self-serve tools and curated datasets that empower non-analysts to explore data and answer their own questions independently.
• • Utilize advanced SQL skills daily to extract, transform, and analyze data, taking ownership of data quality from initial data collection through to the final analysis and reporting stages.
• • Leverage Python or R for advanced statistical modeling, machine learning, and data manipulation tasks, ensuring robust and scalable analytical solutions.
• • Apply a strong foundation in statistics and machine learning, including regression, classification, time series analysis, and experimental design, to solve complex business problems.