Manager 2, Business Data Analytics

The Customer Success (CS) Services Analytics team has an exciting opportunity to improve customer experiences through operational business performance improvements, leveraging data and analytics. We are seeking an exceptional Senior Manager, Business Performance Analysis leading a team of 4-6 talented business data analysts/scientists to work alongside with business stakeholders to deliver operational insights and recommendations. This is an exciting time to join Customer Success at Intuit as we are building a service platform to help our customers beyond core product use. This is your opportunity to join this exciting and transformational journey.

Responsibilities

• Leads and nurtures a team of talented analysts and scientists with a focus on expert performance, expert skills and profile, and operational performance

• Partners with business leaders (e.g., Service Delivery, Operations, Learning & Development, Expert Engagement) to define business strategies, areas of investment, and critical priorities.

• Translates business and analytics strategies into multiple short-term and long-term projects, and manages end-to-end execution.

• Activates analytics insights that lead to decisions or better hypotheses, and evangelizes innovative analytics ideas that enable new opportunities.

• Drives analytics rigor by inspecting and experimenting methodologies, improving techniques, and creating a learning culture.

• Drives data roadmap from data quality to data visualization, and marshals resources from multiple functions to deliver scalable solutions.

• Developing and executing business intelligence strategies that drive business growth through the effective use of data analytics, data visualization, and reporting.

• Role-models "win-together" while challenging status quo and driving changes across teams regardless of organizational structure.

• Examples of deliverables:

• Data insights to inform the future: development of KPIs, business performance diagnostics, expert profile analyses, self-service analytics, and etc. to drive actionable expert/operations insights.

• Data products to transform expert experiences: data predictions, propensity modeling, and etc. to make expert and operator experiences more intelligent with data.