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Sr Data Analyst, Customer Operations
- Jacksonville, Florida, United States
- Jacksonville, Florida, United States
Über
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 have the unique opportunity to 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. You will also 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. You 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. 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 to $146,000. In the United States, outside of California, the reasonably expected salary range is between $80,000 to $138,500. In Canada, the reasonably expected salary range is between $101,500 CAD to $129,500 CAD. 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. Working at Scribd, Inc.
Are you currently based in a location where Scribd, Inc. can employ you? Employees must have their primary residence in or near one of the following cities. This includes surrounding metro areas or locations within a typical commuting distance: 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 at Scribd, Inc.
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 Get to Know Scribd, Inc.
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 accommodations@scribd.com at any point in the interview process. If you apply for a job with Scribd or otherwise engage with us in connection with employment, the personal information we process in that context is subject to our Employee and Applicant Privacy Policy. Scribd, Inc. is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.
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Sprachkenntnisse
- English
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