Data Analyst

Stripe is a financial infrastructure platform for businesses. The Data Analyst will partner with teams across Stripe to develop models, data products, metrics, pipelines, dashboards, and reports that support decision-making and responsible growth. The role will also translate business needs into data problems and deliver actionable recommendations through analysis and data storytelling.

Responsibilities:

• In this role, you'll partner deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly
• You'll work closely with partners to extract insights from the rich and complex data at Stripe
• You'll also work with leaders to translate business needs into data problems
• You'll build metrics, scalable data pipelines, dashboards, and reports to inform and run the business
• You'll deliver actionable business recommendations through analyses and data storytelling

Requirements:

• MS or MA plus 6 years, or BS or BA plus 8 years, of full-time experience exclusive of internships in Business Intelligence Engineering, Data Analyst, and Business Analyst roles
• Proficiency in SQL
• Proven ability to manage and deliver on multiple projects with great attention to detail
• Ability to clearly communicate results and drive impact
• Ability to design, implement, and maintain data pipelines and dashboards to generate actionable insights based on stakeholder requirements
• Experience collaborating with cross-functional teams to deliver strategic insights, benchmarks, and analyses that provide recommendations
• Ability to enable stakeholders and partners by building self-service tooling and providing training to empower stakeholder teams to be data literate and self-sufficient in autonomous reporting capabilities
• Prior experience at a growth-stage internet or software company
• Experience with distributed data frameworks like Spark to write and debug data pipelines
• Good understanding of development processes and best practices like engineering standards, code reviews, and testing
• Strong statistical knowledge
• Working knowledge of Python
• Experience creating leadership-level reporting, such as QBRs and MBRs
• Proficiency with AI tools to accelerate model development, analysis, and coding