Senior Data Analyst, Customer Operations

About the role

This posting reflects an approved, open position within the organization.

Responsibilities

• Build the CS Analytics function and own analytics and operational insights for the department.
• Partner closely 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.
• Translate ambiguous questions into clear measurement frameworks, forecasting models, and actionable reporting.
• Help the organization adopt AI-enabled analytics and automation to reduce manual work, improve decision quality, and establish strong measurement and governance.

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

• 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

• 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

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.