Senior Data Analyst, Customer Operations

About Scribd Scribd, Inc. is on a mission to advance human understanding. Our four products — Scribd®, Slideshare®, Everand™, and Fable — help billions of people across the globe move beyond access and into insight, application, and expertise. We support a culture where employees can be real, bold, debate and commit while embracing plot twists, and where every employee is empowered to take action as we prioritize the customer. We believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in‑person moments that strengthen collaboration and culture. Occasional in‑person attendance is required for all employees, regardless of location. About the Team and Role Scribd is evolving from one of the world’s largest document libraries into a platform where active knowledge building happens. With a library of 300 million documents and over 250 million monthly visitors, our next chapter focuses on helping users move from simply finding information to building deep, actionable understanding. As the first Senior Data Analyst embedded in Customer Operations you will build the CS Analytics function and own analytics and operational insights for the department. You will 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. In this role, you will translate ambiguous questions into clear measurement frameworks, forecasting models, and actionable reporting, and help the organization adopt AI‑enabled analytics and automation to reduce manual work, improve decision quality, and establish strong measurement and governance. About You You are a deeply analytical thinker who is curious and loves to solve problems. You are comfortable 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. You Care Deeply About Building trusted datasets, definitions, and reporting that teams can rely on. Turning ambiguous questions into structured analyses and measurable hypotheses. Creating operational metrics and dashboards that are easy to use and drive action. Applying AI thoughtfully, with clear success metrics and appropriate governance. You Will Own Customer Success and Customer Operations measurement Define and maintain core metrics and business definitions across the customer lifecycle, including onboarding milestones, time‑to‑value, engagement, customer health, renewals, expansions, and churn. Create clear documentation and enable consistent interpretation across Customer Success Operations, RevOps, Finance. Establish instrumentation and data quality requirements with Data Engineering to ensure reliable sources of truth. Build decision‑ready reporting and self‑serve analytics Build 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. Customer retention, churn, and expansion analytics Define and maintain retention metrics, including logo and revenue churn, GRR and NRR, renewal rates, and cohort retention. Build and operationalize churn and renewal risk analyses and models that surface leading indicators. Develop and iterate on customer health scoring frameworks that combine usage, lifecycle events, support signals, billing signals, and qualitative inputs. Forecasting and capacity planning 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. Define evaluation 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. AI‑enabled automation and productivity 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. Define success metrics and guardrails for AI‑supported analytics, including accuracy, coverage, bias considerations, data privacy, and appropriate human review. Drive adoption through enablement, feedback loops, and iteration with cross‑functional partners. Cross‑functional partnership and storytelling 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. Build strong relationships with CS, Customer Ops, RevOps, Finance, Support, and Data teams to align priorities and execute effectively. You Have 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. Nice to Have 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. Compensation In the state of California, the reasonably expected salary range is between $97,000 to $146,000. In the United States, outside of California, the range is between $80,000 to $138,500. In Canada, the range is between $101,500 CAD to $129,500 CAD. The position is also eligible for a competitive equity ownership and a comprehensive benefits package. Location Requirements United States: Atlanta, Austin, Boston, Dallas, Denver, Chicago, Houston, Jacksonville, Los Angeles, Miami, New York City, Phoenix, Portland, Sacramento, Salt Lake City, San Diego, San Francisco, Seattle, Washington D.C. Canada: Ottawa, Toronto, Vancouver Mexico: Mexico City 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 Retirement 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 EEO Statement We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing View email address on click.appcast.io about the need for adjustments at any point in the interview process. 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