Sr Data Analyst, Customer OperationsScribd • San Francisco, California, United States

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Sr Data Analyst, Customer Operations

Scribd

San Francisco, California, United States

San Francisco, California, United States

Apply Now

About

Culture at Scribd, Inc. We support a culture where our employees can be real and be bold; where we debate and commit as we embrace 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 Scribd, Inc. employees, regardless of location. So what are we looking for in new team members? At Scribd, Inc., we hire for "GRIT." Traditionally defined as the intersection of passion and perseverance toward long‑term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude. 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 Senior Analytics Lead you will own analytics and operational insights for the Customer Operations organization. You will partner closely with Customer Operations leadership and 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. Strong SQL skills and experience working with analytical datasets and BI tools (Looker, Tableau, etc.), with an emphasis on performance, usability, and metric governance. 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. Familiarity with tools such as Forethought (AI) and Zendesk. 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 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. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Working at Scribd, Inc. Employees must have their primary residence in or near one of the following cities: 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 Equal Opportunity 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.
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San Francisco, California, United States

Languages

English

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