Senior Data Analyst, Customer Operations

About the role

The Senior Data Analyst will play a pivotal role in building the CS Analytics function at Scribd, Inc. They will partner with Customer Operations leadership and teams to build trusted reporting, improve operational rhythms, and drive measurable outcomes across various customer metrics.

Responsibilities

• Translate ambiguous questions into clear measurement frameworks, forecasting models, and actionable reporting.
• Help the organization adopt AI-enabled analytics and automation to reduce manual work, improve decision quality, and establish strong measurement and governance.
• Own Customer Success and Customer Operations measurement, defining and maintaining core metrics and business definitions across the customer lifecycle.
• Create operational metrics and dashboards that are easy to use and drive action.
• 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.
• 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.
• Evaluate and implement AI or LLM-enabled analytics workflows, including quality measurement and human-in-the-loop processes.
• Develop and iterate on customer health scoring frameworks that combine usage, lifecycle events, support signals, billing signals, and qualitative inputs.
• Build and operationalize churn and renewal risk analyses and models that surface leading indicators.
• Forecast and capacity planning, building 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, ensuring forecasts remain reliable over time.

Requirements

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.

You have experience working in a B2C subscription or membership-based business, with hands-on familiarity with subscription metrics like LTV, churn, refund rate, and renewal rates.

You have strong SQL skills and experience working with analytical datasets and BI tools (Looker, Tableau, etc.), with an emphasis on performance, usability, and metric governance.

You have experience with Python (or similar) for analysis, forecasting, and modeling.

You have a track record of building retention, churn, renewal risk, forecasting, or related analyses and translating outputs into business action.

You have a strong foundation in statistics and experimental thinking, including hypothesis testing and measurement design.

You have strong communication skills, with the ability to influence stakeholders across technical and non-technical teams.

You are comfortable working independently in an environment with evolving priorities.

Qualifications

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.

You turn ambiguous questions into structured analyses and measurable hypotheses.

You create operational metrics and dashboards that are easy to use and drive action.

You apply AI thoughtfully, with clear success metrics and appropriate governance.

Skills

You have experience with customer health scoring, churn modeling, retention and expansion analytics, or lifecycle analytics.

You have experience with analytics engineering practices (for example dbt-style testing, documentation, and semantic layers).

You have experience evaluating or implementing AI or LLM-enabled analytics workflows, including quality measurement and human-in-the-loop processes.

You are familiar with SaaS subscription metrics, cohort analysis, and billing systems.

You have proficiency with Zendesk or similar customer support platforms, and comfort working directly in support tooling to extract and analyze operational data.

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.

We offer a comprehensive and generous benefits package, including Scribd Flex (flexible work model), comprehensive health, dental, and vision coverage, mental health support and disability coverage, generous paid time off, 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, and more.