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Data Analyst
- 給与
- 記載なし
- 勤務地
- 記載なし
- 休日
- Every Sat/Sun
- 雇用形態
- 正社員
どんな仕事かAIによる生成
As a Data Analyst in PayPay's Product Division, this role uses data from users and merchants to support product decision-making and improve user engagement and usage frequency. The responsibilities include analysis and KPI monitoring, creating visualizations and data warehouses, and collaborating with product and business teams.
この求人に応募
応募資格
必須
- 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 to understand and measure business goals while proactively identifying business opportunities.
- Proven ability to build trust and relationships with diverse stakeholders.
歓迎
- Experience in promoting a data-driven culture within a company.
- Analysis experience using large-scale data.
- Experience in building data warehouses/data marts.
- Experience in the payments, financial technology, or e-commerce space.
- Management experience within an analyst organization.
- Japanese language skills.
使用ツール
募集要項最終確認 11/8
- 職種
- データアナリスト
- 雇用形態
- Full Time
- 給与
- 記載なし
- 給与の詳細
- Annual salary paid in 12 installments (monthly)Based on skills, experience, and abilitiesReviewed once a yearLate overtime allowance
- 手当
- Late overtime allowance
- 勤務地
- 記載なし
- 働き方
- Hybrid Workstyle※ You will be expected to work in the office, in alignment with organizational guidelines and team objectives.
- 勤務時間
- Super Flex Time (No Core Time)In principle, 9:00am-5:45pm + 1h break (actual working hours: 7h45m + 1h break)
- 休日・休暇
- Every Sat/SunNational holidays (In Japan)New Year's breakCompany-designated Special daysAnnual leave (up to 14 days in the first year, granted proportionally according to the month of employment. Can be used from the date of hire)Personal leave (5 days each year, granted proportionally according to the month of employment）＊PayPay's own special paid leave system, which can be used to attend to illnesses, injuries, hospital visits, etc., of the employee, family members, pets, etc.
- 福利厚生
- 401KTranslation/Interpretation supportVISA sponsor + Relocation support
- 社会保険
- Social Insurance (health insurance, employee pension, employment insurance and compensation insurance)
- 経験年数
- 3年以上
- 掲載日
- 2026/10/28 01:08（13日前）
- 最終確認
- 2026/11/08 18:11（2日前）
仕事内容
About the role
- As a Data Analyst in the Product Division at PayPay, you will play a crucial role in enhancing our ecosystem's convenience and profitability. Leveraging the vast amounts of data from over 75 million users and millions of merchants nationwide, you will drive increased user engagement and usage frequency, thereby contributing to PayPay's growth and revenue.
Responsibilities
- Collaborate with product managers and executives to support data-driven decision-making with reliable data analysis and deliver actionable insights.
- Proactively analyze data to answer key questions for stakeholders, verify independent ideas and competitive examples, and make suggestions for product and function development and improvement.
- Design and propose product KPIs, creating and maintaining dashboards, and monitoring relevant data.
- Contribute to data-driven processes and initiatives, 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 it easy for anyone to utilize product data.
- 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, and GitHub.
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