Head of Data Science & Analytics, Block

• 8 years of analytics and data science experience
• 3+ years in people management; you have hired and developed high-performing teams
• Team management and cross-functional collaboration skills, including executive communication, data-driven storytelling and prioritization
• Experience leading data science infrastructure strategy and implementation and familiarity with data warehouse design, development, and best practices
• Experience in experiment design
• Expertise with SQL, Python and data visualization tools (i.e., Looker, Tableau, Thoughtspot)

Desirable

• We are looking for a experienced leader to manage a newly centralized Data Science and Analytics team
• You will help shape our data strategy, establish excellence in solving business problems and develop insights that guide our roadmap, design decisions and marketing strategies across our artist and fan platforms
• Be a leader:
• Build and manage a high-performing team of analysts and data scientists
• Establish the data and analytics team as a trusted partner for teams across the organization, partnering with them to solve complex business problems and provide recommendations based on insights
• Influence the data community throughout TIDAL and establish connections with Block foundational engineering teams to leverage best practices and advocate for support
• Grow the analytics and data science discipline:
• Play a critical role in helping our engineering and product teams make data-driven decisions to build best-in-class products and thoughtful features
• Foster an environment that enables the team to execute quickly while maintaining a high standard for quality
• Provide thought leadership in capturing and structuring large data sets to create unified views of the subscriber, subscriber behavior, and other data points
• Own the TIDAL analytics roadmap including improving capabilities, infrastructure and tools
• Drive execution:
• Drive the design and delivery of analytics deliverables – dashboards, deep-dive analysis, measurement frameworks, attribution rigor, segmentation valuation, conversion funnel insights, and value measurement (LTV), etc
• Develop efficient processes, ensuring the team is operating with high velocity, ownership, and self-accountability
• Provide mentorship to team members through feedback, coaching, and hands-on technical guidance
• Translate ambiguous, unstructured business problems into actionable data-driven analyses
• Communicate analysis and insights to high-level partners and executives in verbal, visual, and written media
• Build and maintain critical data infrastructure alongside our dedicated data engineering team