Senior Data Analyst, Customer Operations

About the role

The Senior Data Analyst will build the CS Analytics function and own analytics and operational insights for Customer Operations. They will partner with Customer Operations leadership & team, Product, Finance (RevOps), and Data Engineering to build trusted reporting, improve operational rhythms, and drive measurable outcomes across retention, expansion, customer health, and support efficiency.

Responsibilities

• Translate ambiguous questions into clear measurement frameworks, forecasting models, and actionable reporting.
• Create operational metrics and dashboards that are easy to use and drive action.
• Apply AI thoughtfully, with clear success metrics and appropriate governance.
• Own Customer Success and Customer Operations measurement.
• Define and maintain core metrics and business definitions across the customer lifecycle.
• Create clear documentation and enable consistent interpretation across Customer Success Operations, RevOps, Finance.
• Instrumentation and data quality requirements with Data Engineering to ensure reliable sources of truth.
• Build decision-ready reporting and self-serve analytics.
• Enable self-serve analytics with clear definitions, drill paths, and actionable views for CS leaders, managers, and operators.
• Create automated reporting and proactive alerting for KPI movement and risk signals.
• Partner with Customer Operations to translate forecasts into staffing plans, coverage models, and operating cadences.
• Identify and prototype AI-driven workflows that reduce manual analysis and speed up decision-making.
• Evaluate and implement AI or LLM-enabled analytics workflows, including quality measurement and human-in-the-loop processes.
• Develop and iterate on customer health scoring frameworks.
• Build and operationalize churn and renewal risk analyses and models.
• Forecast and capacity planning.
• Translate Customer Success Operations questions into structured analyses and measurable hypotheses.
• Communicate insights with clear narratives that influence decisions across technical and non-technical audiences.

Requirements

• 4+ years of experience in analytics, business operations, or business intelligence roles, ideally supporting Customer Success, Customer Operations, RevOps, Support, Sales, Growth, or similar customer-facing functions.
• Experience working in a B2C subscription or membership-based business (e.g., SaaS, media, streaming, or consumer subscription).
• Strong SQL skills and experience working with analytical datasets and BI tools (Looker, Tableau, etc.), with an emphasis on performance, usability, and metric governance.
• Comfortable working within an existing Databricks environment, reading gold-layer schemas, running queries, and working with Data Engineering to understand what data is available and how to use it.
• Experience with Python (or similar) for analysis, forecasting, and modeling.
• A track record of building retention, churn, renewal risk, forecasting, or related analyses and translating outputs into business action.
• A strong foundation in statistics and experimental thinking, including hypothesis testing and measurement design.
• Strong communication skills, with the ability to influence stakeholders across technical and non-technical teams.
• Comfort working independently in an environment with evolving priorities.

Qualifications

• Experience with customer health scoring, churn modeling, retention and expansion analytics, or lifecycle analytics.
• Experience with analytics engineering practices (for example dbt-style testing, documentation, and semantic layers).
• Experience evaluating or implementing AI or LLM-enabled analytics workflows, including quality measurement and human-in-the-loop processes.
• Familiarity with SaaS subscription metrics, cohort analysis, and billing systems.
• Proficiency with Zendesk or similar customer support platforms, and comfort working directly in support tooling to extract and analyze operational data.

Skills

• Deeply analytical thinker who is curious and loves to solve problems.
• Comfort operating in a fast-moving environment with evolving priorities.
• Combine strong technical skills with an operator’s mindset and can communicate clearly with both technical and non-technical partners.
• Care deeply about building trusted datasets, definitions, and reporting that teams can rely on.
• Turn ambiguous questions into structured analyses and measurable hypotheses.
• Create operational metrics and dashboards that are easy to use and drive action.
• Apply AI thoughtfully, with clear success metrics and appropriate governance.

Benefits

At Scribd, Inc., your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. Benefits include:

• Scribd Flex (flexible work model)
• Comprehensive health, dental, and vision coverage
• Mental health support and disability coverage
• Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals
• Paid parental leave and family support benefits
• Retailment matching and employee equity
• Learning and development programs and professional growth opportunities
• Wellness and home office stipends
• Complimentary access to the Scribd, Inc. suite of products
• Enterprise access to leading AI tools