Intuit Inc.
Group Manager, Business Data Analytics (Data Science)
Intuit Inc., San Diego, California, United States, 92189
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 Group Manager, Business Performance Analysis leading a team of ~10 talented business data analysts/scientists to work alongside 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.Creates network wide KPI/metrics strategy and tiered framework for evaluating the quality, delivery, and productivity of our experts, managers, and operators.Integrates AI/ML into the insights workflow to both automate repetitive tasks and increase the depth of insights into conversational data.Evangelizes the use of statistical methods to monitor and describe business performance, predict future outcomes via modeling.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 architecture to data visualization, and marshals resources from multiple functions to deliver scalable solutions.Develops and executes 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, etc. to drive actionable expert/operations insights.Data products to transform expert experiences: data predictions, ARIMA modeling, propensity modeling, etc. to make executive leader, manager, and operator decisions more intelligent with data.
Minimum Requirements
15+ years of diverse analytics experience on end-to-end service and/or operational data (e.g. millions of service contacts).Thrive within a high-paced, high-growth environment.Proven experience in leading a team of analysts and/or scientists.Expert in driving weekly, structured, tiered KPI reviews; generating insights that can be used to improve service/operational performance.Full stack data analytics/science experience, including data sourcing, diagnostic analysis, predictive/prescriptive modeling/analysis.Strong passion for uncovering strategic opportunities and solving business problems.Proficient with SQL, Python, and generative AI integration into data products.Deep experience in statistical modeling techniques, including Hierarchical/Mixed Effects Modeling.Outstanding communication skills, presenting data stories that drive action and impact to both technical and non-technical/business stakeholders.Undergraduate degree a must. Masters in a quantitative discipline preferred.
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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.Creates network wide KPI/metrics strategy and tiered framework for evaluating the quality, delivery, and productivity of our experts, managers, and operators.Integrates AI/ML into the insights workflow to both automate repetitive tasks and increase the depth of insights into conversational data.Evangelizes the use of statistical methods to monitor and describe business performance, predict future outcomes via modeling.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 architecture to data visualization, and marshals resources from multiple functions to deliver scalable solutions.Develops and executes 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, etc. to drive actionable expert/operations insights.Data products to transform expert experiences: data predictions, ARIMA modeling, propensity modeling, etc. to make executive leader, manager, and operator decisions more intelligent with data.
Minimum Requirements
15+ years of diverse analytics experience on end-to-end service and/or operational data (e.g. millions of service contacts).Thrive within a high-paced, high-growth environment.Proven experience in leading a team of analysts and/or scientists.Expert in driving weekly, structured, tiered KPI reviews; generating insights that can be used to improve service/operational performance.Full stack data analytics/science experience, including data sourcing, diagnostic analysis, predictive/prescriptive modeling/analysis.Strong passion for uncovering strategic opportunities and solving business problems.Proficient with SQL, Python, and generative AI integration into data products.Deep experience in statistical modeling techniques, including Hierarchical/Mixed Effects Modeling.Outstanding communication skills, presenting data stories that drive action and impact to both technical and non-technical/business stakeholders.Undergraduate degree a must. Masters in a quantitative discipline preferred.
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