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.
• Create and iterate on dashboards, KPI scorecards, and operational reporting that support day-to-day execution and executive visibility.
• 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, such as drops in engagement, support spikes, onboarding delays, and renewal risk.
• Develop and iterate on customer health scoring frameworks that combine usage, lifecycle events, support signals, billing signals, and qualitative inputs.
• Build forecasting models for key planning needs such as renewal volume, renewal risk, churn, expansion pipeline, ticket volume, and staffing capacity for our BPO partner.
• Evaluate and implement AI or LLM-enabled analytics workflows, including quality measurement and human-in-the-loop processes.
• Partner with Customer Operations to translate forecasts into staffing plans, coverage models, and operating cadences.

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), with hands-on familiarity with subscription metrics like LTV, churn, refund rate, and renewal rates.
• 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

• Comfort 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 analytics engineering practices (for example dbt-style testing, documentation, and semantic layers).
• 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.
• Combines strong technical skills with an operator’s mindset and can communicate clearly with both technical and non-technical partners.
• Carefully builds trusted datasets, definitions, and reporting that teams can rely on.
• Turns ambiguous questions into structured analyses and measurable hypotheses.
• Creates operational metrics and dashboards that are easy to use and drive action.
• Applies AI thoughtfully, with clear success metrics and appropriate governance.

Benefits

• 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.
• Retailer 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.

Pay

The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply.

Schedule

Occasional in-person attendance is required for all Scribd, Inc. employees, regardless of location.