Senior Data Analyst, Codecademy

• Reputation as a user-obsessed data and analytics expert
• Minimum of 5 years in an analytical role focused on digital product, edtech, or subscription-based product analytics
• Expertise with SQL and hands-on experience with modern BI tools like Looker, Tableau, PowerBI, etc
• Some exposure to modern analytics engineering development tools, processes, and workflows like dbt, Apache Airflow, git & version control, Jira, etc
• Hands-on experience supporting the development, execution, and analysis of product experimentation (A/B/n testing, pre-post analysis, etc.)
• Strong problem-solving skills to determine how to best employ multiple data sets and analytical methods to answer user and product development questions
• The ability to prioritize and effectively manage the support of multiple overlapping projects, ad-hoc requests, and general data and analytics support
• A “Founder” mentality - relentless, resourceful, proactive, and results-oriented
• Experience communicating the results of an analysis or experiment to a wide variety of audiences
• Working knowledge of customer data platforms like Segment
• Clear and concise written and verbal communication skills
• Ability to handle multiple priorities and tight timelines
• Strong track record of establishing trusted relationships

Desirable

• Develop an expert understanding of how learners engage with Codecademy and use that expertise to advocate for our learners across the organization
• Partner with stakeholders to design and implement analytics strategies to support their development and business needs
• Play a critical role in supporting and leading all things product experimentation at Codecademy
• Contribute to our analytics infrastructure by turning complex and sometimes ambiguous business requirements into effective, scalable data models, analysis, and reporting
• Identify opportunities for improvements, contribute to our documentation, and collaborate with the team and our end-users to develop and apply analytics and experimentation best practices
• Collaborate with Data Science and Data Engineering Team Members on a wide range of projects
• Apply software engineering best practices to your analytics workflow (ex: version control, testing)
• Develop and maintain effective reporting in Looker and other BI tools to help stakeholders better understand our users and their businesses
• Ensure product developments and changes integrate well with our existing data models and reporting tools, and when they don’t, build the necessary capabilities to adjust