Machine Learning Engineer, Credit Modeling

PayPay Minato-ku, Tokyo
  • 💴 No salary range given
  • 🏡 Fully remote (within Japan)
  • 🧪 3+ years experience required
  • 💬 No Japanese required
  • 🌏 Apply from abroad
  • 🧳 Relocate to Japan
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About PayPay

PayPay Minato-ku, Tokyo

With over 65M million registered users (as of August 2024), PayPay is the country’s most popular mobile wallet used by approximately one out of every two smartphone users in Japan.

Key benefits

  • International engineering team
  • Japanese lessons on company time
  • Incredible scale

About the position

We are seeking an experienced Machine Learning Engineer with a strong background in end-to-end ML systems, cloud platforms, data pipelines, and model monitoring. Lead the development of cutting-edge machine learning software systems for credit modeling and default risk prediction. Your work will not only involve deploying these systems to production but also ensuring they meet the diverse needs of our users and merchants through rigorous testing.

Imagine working with petabyte-scale datasets, developing high-throughput, low-latency systems that serve models in production, and touching the lives of over 65 million customers daily. Collaborate with some of the most innovative engineering teams to bring machine learning functionalities into our in-house production systems, and watch your contributions make a tangible difference.

Responsibilities

  • Design and implement credit ML models and systems, ensuring robust and scalable solutions.
  • Develop end-to-end ML pipelines for credit modeling, including data collection, preprocessing, model training, and deployment.
  • Collaborate with data scientists and software engineers to integrate ML models into production environments, enhancing lending systems.
  • Utilize cloud platforms (AWS preferred, GCP, Azure) to scale ML solutions, manage resources, and optimize costs.

Requirements

  • 3+ years of professional experience, particularly in developing and implementing credit ML models or systems within the banking or FinTech industry.
  • Educational background in Computer Science, Engineering, Mathematics or related field.
  • Good understanding of supervised and unsupervised learning, deep learning, reinforcement learning, and ensemble methods.
  • Proficiency in Python, PostgreSQL, Java/Scala.
  • Strong knowledge of database management systems (e.g., MySQL, PostgreSQL), data wrangling, feature engineering, ETL processes, and SQL databases.
  • Familiarity with tools such as Apache Spark.
  • Experience with Docker, Kubernetes, and cloud platforms.
  • Knowledge of MLOps practices.
  • Expertise in TensorFlow, PyTorch, Keras, scikit-learn, and XGBoost.
  • Proficiency with Jupyter Notebooks, Git, Jenkins, Apache Spark, and Hadoop.

Nice to haves

While not specifically required, tell us if you have any of the following.

  • Japanese language skills.
  • AWS experience.
DO YOU NEED MORE INFO?
ASK A QUESTION

Meet PayPay's Developers

Ashwini leads one of PayPay’s payment sub-teams. She got there by doing something she’s done throughout her career: identifying something she wants to do and asking to do it.

Read her story...
Photo of Yoseph Savianto

iOS Development at PayPay

with Yoseph Savianto

Yoseph joined PayPay after being attracted to their mission of making Japan a cashless society. As an iOS Engineer, he originally joined their iOS feature team, but now works on their platform team, creating an internal SDK for their iOS and Android apps.

Read his story...

Shilei started working on PayPay before it launched, and has seen it grow into a product used by tens of millions of users. He explains how diversity has helped them overcome challenges, and what PayPay is looking for in candidates.

Read his story...
Photo of Adrian Mariadas

Refactoring PayPay’s Android App

with Adrian Mariadas

Adrian came to Japan to join PayPay as an Android Engineer. As the app has grown in scope, refactoring the codebase to ensure development can continue at a rapid pace has been a big part of his job.

Read his story...

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