データサイエンティスト （与信領域）

Job Description

PayPay Card is seeking a Data Scientist to join its Credit Risk team. The company was established in 2021 to provide user-friendly fintech services, integrated with the PayPay payment platform, which has over 69 million users as of May 2025. PayPay Card aims to revolutionize credit services and create a future beyond current expectations.

The Data Scientist will be part of the Screening Planning Department, which focuses on driving transformation through data and digital technology. The Screening Analysis Department, consisting of 10 members, conducts advanced data analysis using AI and machine learning to apply insights to business operations. The role involves extracting and resolving issues in screening and debt collection, contributing to significant profit improvements.

Role Involves:

• Conducting advanced analysis using statistical and machine learning techniques in the credit risk domain.
• Applying analysis results to business operations.
• Collaborating with PayPay members and internal teams on credit risk-specific projects.
• Identifying and resolving issues in screening and debt collection.

Requirements:

• Practical experience in programming (either Python or SQL).
• Experience in advanced analysis using machine learning and applying the results to business operations.
• OR experience as a consultant, providing support for solving corporate issues through advanced analysis using machine learning.

The role offers:

• Opportunity to work with large-scale data through collaboration with PayPay and LINE Yahoo.
• High contribution to the business with the ability to feel the economic effect of model creation and measures developed using data science.
• Career advancement opportunities, including management positions and specialist roles as a data scientist.
• Experience in high-impact projects directly linked to the company's profits in a fast-paced environment.
• Utilization of machine learning tools such as DataRobot and DWH such as GCP, actively incorporating technologies for automation and accuracy improvement.
• A hybrid work style that balances remote work with office presence.