Machine Learning Engineer, Credit Modeling at PayPay

PayPay is seeking a Machine Learning Engineer to contribute to its credit modeling and default risk prediction systems. The role involves the end-to-end development of ML pipelines, ensuring the systems are scalable and robust to meet user and merchant needs. The Machine Learning Engineer will be working with petabyte-scale datasets for over 65 million customers daily.

The Machine Learning Engineer will work closely with data scientists and software engineers to enhance credit lending systems.

Responsibilities:

• Designing and implementing credit ML models and systems.
• Developing end-to-end ML pipelines for credit modeling.
• Integrating ML models into production environments.
• Utilizing cloud platforms (AWS preferred, GCP, Azure) to scale ML solutions.

Requirements:

• 3+ years of experience in developing and implementing credit ML models.
• Educational background in Computer Science, Engineering, Mathematics, or related field.
• Good understanding of supervised and unsupervised learning.
• Proficiency in Python, PostgreSQL, Java/Scala.
• Strong knowledge of database management systems.
• Familiarity with tools such as Apache Spark.
• Experience with Docker, Kubernetes, and cloud platforms (AWS preferred).
• Knowledge of MLOps practices.
• Expertise in TensorFlow, PyTorch, Keras, scikit-learn, and XGBoost.
• Proficiency with Jupyter Notebooks, Git, Jenkins, Apache Spark, and Hadoop.

PayPay offers:

• Social Insurance (health insurance, employee pension, employment insurance and compensation insurance)
• 401K
• Translation/Interpretation support
• VISA sponsor + Relocation support