Senior Data Analyst, Customer Operations

About this role

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.

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.

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

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 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…