Data Analyst

Position Overview

• Location Type: Not Specified
• Employment Type: Not Specified
• Salary: Not Specified

PayPay is a FinTech company with over 65 million users (as of August 2024). The company's vision is "Unlimited," emphasizing risk-taking, innovation, and growth. They are seeking individuals who can embrace challenges and contribute to PayPay's expansion.

About the Role

As a Data Analyst in the Product Division, you will be instrumental in enhancing PayPay's ecosystem by leveraging data from over 65 million users and 2.35 million merchants. Your goal is to drive increased user engagement and usage frequency, directly contributing to PayPay's growth and revenue.

Responsibilities

• Collaborate with product managers and executives to support data-driven decision-making through reliable data analysis and actionable insights.
• Proactively analyze data to answer key questions for stakeholders, validate ideas, and suggest product and function improvements.
• Design and propose product KPIs, create and maintain dashboards, and monitor relevant data.
• Contribute to data-driven processes, including knowledge sharing, rule creation, stakeholder support, and education.
• Develop clear documentation and educational materials, and identify opportunities for improvement.
• Create and maintain rich interactive visualizations through data interpretation and analysis from multiple data sources.
• Interact cross-functionally with product, business planning, marketing, and sales teams to share analytical knowledge and collaborate on projects.
• Design and build data warehouses and data marts for responsible products, making data easily accessible for utilization.
• Evangelize a data-driven culture throughout the organization, improving experimental/test design, contributing to best practices, and partnering with stakeholders and data partners.

Technical Environment

• BigQuery
• LookerStudio
• JupyterLab
• Google Analytics
• dbt
• GitHub

Qualifications

• At least 3 years of experience in data analysis.
• Expertise in statistics (understanding of correlation, causation, various tests, etc.).
• Skills in designing, validating, visualizing, and reporting A/B tests.
• Demonstrated ability to generate data insights.