Senior Data Analyst - Customer Operations

Overview

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 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.

As a Senior Customer Operations Data Analyst, you will play a pivotal role in analyzing support data (primarily through tickets and user feedback) to understand issues and insights, enhance decision-making, and improve the overall user experience. You will work closely with cross-functional teams to uncover root causes of customer support challenges and opportunities. The ideal candidate is a self-starter who thrives in fast-paced and ever-changing environments.

You should be a passionate advocate for improving the customer journey through data-driven insights.

As Scribd’s first formal analytics hire for the Customer Support team, this is a unique opportunity to shape and drive the analytics function within the department. You will be responsible for gathering, synthesizing, and improving insights across all functions of Customer Support. This includes collaborating with and mentoring peers, as well as hands-on work to collect and analyze data related to key metrics such as SLAs, QA, contact rate, customer support satisfaction, refunds, churn, and cost-to-support.

You will play a pivotal role in ensuring that data-driven insights are used to enhance decision-making and improve the overall user experience.

• Data Collection, Synthesis, and Analysis: Gather, analyze, and interpret data to provide insights on customer support data and trends. Create pipelines for the collection and processing of new data from customer support sources.

• Reporting & Insights: Create comprehensive reports in Databricks, Looker, Google Sheets, Zendesk, and/or similar tools to monitor key metrics.

• Performance Metrics: Evaluate the effectiveness and performance of Customer Support goals, initiatives, and projects. Conduct in-depth analyses of performance, measuring KPIs such as service level achievement, customer effort and satisfaction, and user retention.

• Customer Insights: Analyze customer feedback and behavior patterns in response to product changes and on an ongoing basis.

• Forecasting: Forecast contact volumes and capacity needs.

• Road mapping: Collaboratively manage the Customer Support’s data analysis roadmap with leadership.

• Collaboration: Work cross-functionally with stakeholders across Customer Support, Data & Analytics, Product, Engineering, and User Research.

• Leveraging Technology: Use AI and BI to enhance customer support operations and increase efficiency. Develop and maintain dashboards and reports and own communication of critical marketing metrics and campaign performance to team leads and executive stakeholders.

• Process Improvement: Provide actionable insights to stakeholders through data analysis, and identify opportunities for improvements operational efficiency. Stay informed…