Sr. Manager, Service Strategy & Operations Analytics

Job Description

The Operations Analytics Senior Manager will own the North America Service Strategy & Operations analytics strategy, including the multi-year vision, operating model, governance agenda, and roadmap for data, analytics, and AI-enabled decision support.

This leader will build scalable analytics capabilities, strengthen KPI architecture and data trust, and translate operational, customer, and financial insights into measurable business outcomes and executive recommendations.

Serving as a strategic advisor to senior leaders, the role partners across Operations, Customer Experience, Product, Engineering, and Finance to improve performance visibility, inform operating plans, and shape long-term service delivery strategy.

This is a remote role.

What You'll Do:

Own Operations Analytics Strategy & Operating Model

• Own the North America service operations analytics vision, strategy, multi-year roadmap, operating model, governance, prioritization, and delivery standards.
• Set analytics priorities that inform operating plans, strategic investments, workforce planning, service delivery, and enterprise performance objectives for senior leadership.
• Build and lead Operations Analytics as an enterprise capability, including talent strategy, operating rhythms, standards, roadmap, stakeholder engagement, and capability development.
• Use structured problem-solving and analytics to diagnose performance drivers, root causes, risks, and opportunities across complex operations.
• Establish repeatable performance tracking and variance analysis frameworks aligned to planning cycles and leadership decisions.

Strengthen Data Quality, KPI Architecture and Confidence in Decision Support Tools

• Build scalable data foundations, governance standards, KPI architecture, and analytics capabilities that improve trust, access, and decision-making across operations.
• Develop, coach, and grow a high-performing analytics team while establishing scalable standards and best practices.
• Partner with technical teams to improve data quality, reliability, and accessibility for high-value business use cases.
• Lead enterprise operational reporting, dashboarding, and technology migration with a focus on clarity, actionability, scalability, and reuse.
• Identify, size, prioritize, and track opportunities to improve efficiency, reduce cost, increase productivity, mitigate risk, and enhance customer outcomes.
• Partner with Finance and FP&A to align operational reporting with cost drivers, forecast assumptions, performance metrics, pricing drivers and P&L outcomes.

Drive Analytics, Automation & AI Transformation

• Lead analytics transformation, including self-service analytics and AI-enabled decision support, by defining practical use cases, adoption paths, and scalable standards.
• Expand access to high-value data, tools, and AI-driven solutions while balancing ease of use, governance, reliability, and business value.
• Move the organization from static reporting to dynamic, diagnostic, forward-looking insights that support planning, prioritization, and course correction.
• Build stakeholder confidence and capability in using data for day-to-day decision-making