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.
• Define and maintain retention metrics, including logo and revenue churn, GRR and NRR, renewal rates, and cohort retention.
• 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 approaches such as backtesting, holdouts, calibration, and monitoring, and ensure forecasts remain reliable over time.
• 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, such as automated insights, narrative summaries, anomaly detection triage, and stakeholder Q&A.
• Drive adoption through enablement, feedback loops, and iteration with cross-functional partners.

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.
• 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

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. San Francisco is our highest geographic market in the United States. In the state of California, the reasonably expected salary range is between $97,000 [minimum salary in our lowest geographic market within California] to $146,000 [maximum salary in our highest geographic market within California]. In the United States, outside of California, the reasonably expected salary range is between $80,000 [minimum salary in our lowest US geographic market outside of California] to $138,500 [maximum salary in our highest US geographic market outside of California]. In Canada, the reasonably expected salary range is between $101,500 CAD[minimum salary in our lowest geographic market] to $129,500 CAD[maximum salary in our highest geographic market]. We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. 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. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package.

Pay

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. San Francisco is our highest geographic market in the United States. In the state of California, the reasonably expected salary range is between $97,000 [minimum salary in our lowest geographic market within California] to $146,000 [maximum salary in our highest geographic market within California]. In the United States, outside of California, the reasonably expected salary range is between $80,000 [minimum salary in our lowest US geographic market outside of California] to $138,500 [maximum salary in our highest US geographic market outside of California]. In Canada, the reasonably expected salary range is between $101,500 CAD[minimum salary in our lowest geographic market] to $129,500 CAD[maximum salary in our highest geographic market]. We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. 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.