Chegg provides individualized learning support to students as they pursue their educational journeys. Available on demand 24/7 and powered by over a decade of learning insights, the Chegg platform offers students AI-powered academic support thoughtfully designed for education coupled with access to a vast network of subject matter experts who ensure quality. No matter the goal, level, or style, Chegg helps millions of students around the world learn with confidence by helping them build essential academic, life, and job skills to achieve success.

The Role:

We’re hiring a Senior Product Analyst to help us understand and improve how learners experience our products. You’ll analyze how content, features, and user flows perform in practice—identifying where friction exists, where engagement thrives, and how we can create a more effective and intuitive learning experience.

You’ll partner closely with Product Managers, Learning Scientists, and Engineers to connect insights to action—defining the metrics that matter, instrumenting data pipelines, and translating findings into design and product decisions. Your work will shape how the Product & Applied Learning team builds, measures, and iterates our student experience.

This role is ideal for a self-directed, systems-minded analyst who thrives on uncovering insights that make complex experiences simple and effective for learners.

What You’ll Do:

Partner with Learning Science and Instructional Design to conceptually map how learning model standards—difficulty curves, skill levels, instructional flow—translate into learner outcomes.

Create metrics for learning quality, persistence, and proficiency—moving beyond clicks and usage to identify the metrics that are true predictors of completion and satisfaction.

Develop and maintain dashboards that visualize learner progress, satisfaction, and experience quality, creating a single source of truth for program health.

Partner with Product Managers and Learning Scientists to design and analyze experiments (A/B, multivariate, feature pilots) that measure the impact of new formats, UX improvements, or product features.

Collaborate with Learning Science to link quantitative data with qualitative insights, grounding product design in evidence.

Communicate insights clearly and visually—craft data stories and presentations that turn analysis into actionable narratives influencing decisions and roadmap priorities.

Continuously improve analytics systems—automate processes, refine models, and ensure accuracy and accessibility across teams. Integrate AI as an internal enabler wherever it makes sense.

Drive a culture of user-centric, evidence-based decision-making so every product choice is grounded in data and aligned to learner needs.

Think creatively about how we can leverage data analytics solutions to solve business problems in ways we might not have considered.

Basic Qualifications:

3–6 years of experience in product or business analytics, ideally within a B2C, SaaS, or education context.

Advanced SQL skills and fluency in Python or R for data analysis, modeling, and visualization, and comfortable with integrating AI into methods to support data-driven recommendations & drawing insights.

Strong analytical toolkit—comfortable with A/B testing, funnel analysis, time series, and behavioral modeling.

Proven ability to translate data into actionable product insights.

Experience building dashboards in Tableau, Looker, or a similar visualization tool.

Strong communication skills—able to synthesize complex findings into clear, actionable recommendations.

Collaborative and proactive; comfortable working with Product, Engineering, and Learning teams.

User-centric mindset—curious about how design and data together shape learner outcomes.

Preferred Qualifications:

Experience analyzing engagement or learning data within an edtech, learning, or content platform.

Familiarity with UX research methods or human-centered design.

Knowledge of statistical experimentation, hypothesis testing, and causal inference.

Comfort with working in agile product environments.

Passion for learning analytics, learning science, or experience optimization.