Customer Experience Operations Analyst II ( Power BI / Microsoft Fabric)
Indexed description
Job Responsibilities
Metrics & Reporting
• Define, refine, and operationalize a set of support metrics that reflect both operational health and customer impact (not just volume and SLA)
• Build and maintain dashboards across the Microsoft Fabric ecosystem to provide visibility into:
o Support demand and trends
o Backlog health and case lifecycle
o Escalations and recurring issue patterns
• Evaluate the effectiveness of AI-enabled support capabilities, identifying where outputs are inaccurate, misleading, or fail to support complex support scenarios.
Insights & Analysis
• Analyze support data to identify systemic product issues, friction points, and emerging risks
• Translate complex support activity into clear narratives and recommendations for Product and Engineering
• Partner with Customer Success (Gainsight) to ensure support data contributes meaningfully to:
o Health scores
o CSAT analysis
o Customer risk identification
Data Quality & Structure
• Partner with Support Ops and System Admin to improve:
o Case taxonomy
o Categorization accuracy
o Data completeness and usability
• Identify gaps in data capture and propose pragmatic improvements
Cross-Functional Enablement
• Act as a key partner to Support, Product, and CS teams in understanding support trends
• Support regular business reviews (weekly/monthly) with clear, insight-driven reporting
• Help establish feedback loops between support insights and product improvements
AI & Emerging Capabilities
• Evaluate outputs from AI-enabled tools (e.g., Forethought, Agentforce) to:
o Assess accuracy and usefulness
o Identify opportunities to improve knowledge capture and insights
• Partner with Ops and Systems to ensure AI-generated data is measurable and trustworthy
Job Qualification
• 5–7 years of experience in Support Operations, Business Analytics, or similar roles in a B2B environment
• Strong experience with BI tools within the Microsoft Fabric ecosystem (Power BI, etc.)
• Experience working with Salesforce Service Cloud data models
• Demonstrated ability to work with ambiguous or incomplete datasets
• Experience partnering with Product, Engineering, or Customer Success teams
• Familiarity with Gainsight or similar CS platforms preferred
• Exposure to AI-enabled support tools (e.g., Forethought, Agentforce) is a strong plus
• Strong analytical and storytelling skills—ability to turn data into decisions
What Success Looks Like
• Clear, trusted visibility into support trends and performance
• Support data is actively used to inform product and customer decisions
• Improved alignment between Support, Product, and Customer Success
• Meaningful metrics that reflect real customer experience, not just operational proxies
• High confidence in data quality and reporting consistency
• Clear Metrics for measuring AI effectiveness, and drive for improving those outcomes.
Model N is transforming how Life Sciences companies manage revenue, commercialization, and compliance.
For more than 25 years, Model N has been the leader in end-to-end commercialization, revenue optimization, and compliance for pharmaceutical and medical technology companies.
Our intelligent, cloud-based platform combines technology, data, analytics, AI, and industry expertise to help leading Life Sciences organizations optimize revenue, navigate complex regulations, improve decision-making, and bring life-changing products to market faster.
Today, 150+ leading companies across the globe trust Model N to optimize growth and transform critical commercial processes. Our solutions manage approximately $1.3 trillion in gross revenue, helping customers reduce complexity, strengthen compliance, and unlock new opportunities for growth.
At Model N, we are building the next generation of Life Sciences revenue management—where technology, data, AI, and human expertise come together to create meaningful business impact.
Join us to build technology that powers innovation in Life Sciences and makes a difference at global scale.
For more information, visit www.modeln.com.
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