Senior Data Scientist Credit Modeling

Japanese fintech company operating the PayPay mobile payments service.

Tokyo, Japan
About PayPay Corporation

PayPay Corporation develops and provides electronic payment services, including the PayPay mobile payment platform. It was founded on June 15, 2018, is headquartered in Tokyo, Japan, and currently operates an active financial-services platform integrating payments with card, banking, securities, and insurance offerings.

View jobs by PayPay Corporation

Skills

About the Role

You will lead credit-risk modeling from ambiguous problem definition through model development, evaluation, and impact assessment. You will develop features and models using large datasets, establish rigorous validation standards, estimate financial and customer effects, and guide production deployment and monitoring. You will communicate recommendations and trade-offs, lead technical discussions, mentor data scientists, and improve reusable modeling practices.

Requirements

  • Bachelor’s degree in a quantitative field or equivalent
  • Six or more years of professional data science or applied machine learning experience
  • Statistical modeling
  • Supervised learning
  • Feature engineering
  • Model interpretation
  • Validation and experimentation experience
  • Experience with time-aware evaluation, calibration, bias or selection effects, and post-deployment monitoring
  • Python
  • SQL
  • scikit-learn or XGBoost
  • Experience with large-scale data platforms or distributed data processing
  • Experience building reproducible analysis and model workflows
  • Experience collaborating with engineering teams on deployment and model evaluation after release

Responsibilities

  • Own the scientific approach to modeling work from decision definition through validation and recommendation
  • Develop and evaluate models and features using large and varied datasets
  • Set model evaluation standards and identify leakage, selection bias, delayed outcomes, and calibration needs
  • Estimate effects on revenue, credit losses, exposure, portfolio quality, and customer outcomes
  • Guide models into production and monitor deployed performance and outcomes
  • Communicate findings and trade-offs to technical and non-technical stakeholders
  • Lead technical discussions, review modeling approaches, mentor data scientists, and establish reusable practices

Benefits

  • Social insurance
  • 401K
  • Translation and interpretation support
  • Visa sponsorship
  • Relocation support
  • Super flex time with no core time
  • Annual leave
  • Personal leave