Senior Data Analyst

Role:

Location:

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.

Your analysis will provide valuable insights and identify key levers that materially improve how and what we create, as well as how we manage and deliver our content. Strong communication and analytic skills are critical for success in this role. Curiosity, persistence, creativity, and a desire to understand “the why” will make you successful in this role.

Responsibilities

• Use data and analytical/statistical methods to provide insights into business performance and user journeys and identify areas of leverage
• Core analytics: derive insights on catalog performance, customer engagement with the catalog, and operational performance and trends
• Lead and perform thoughtful and detailed research and analysis to support business cases and prove/disprove hypotheses
• Create optimized queries and configurable data models in Excel, Python, and/or R, develop forecast models, develop and implement impactful reports and dashboards.
• Partner with operations teams, product managers, engineers, and leadership to solve pressing issues
• Support initiative launches by understanding scope, assessing instrumentation needs and driving insights
• Write technical memos that document data processing decisions and summarize the quality of data.
• Analyze and synthesize research findings into key insights for stakeholders
• Extensive experience in descriptive and inferential analysis

Qualifications

• 5+ years of demonstrated success in analytics with large and complex datasets and schemas.
• Master’s degree preferred; technical fields preferred (Math, Statistics, Engineering, Economics, etc).
• Proficiency use statistical programming software such as Python, R.

  (Python is a must)

• Advanced data manipulation, modeling and visualization skills (Tableau, Databricks, Amplitude, API, Excel, Powerpoint)
• Expertise in forecasting/business modeling as well as predictive analysis.
• Conduct qualitative and quantitative research and use mixed-method approaches to data analysis.
• Understanding of Machine Learning concepts
• Ability to pull details from nested data formats/extracts (JSON, Spectrum)