Machine Learning Engineer, Credit Modeling

About PayPay

PayPay, a fintech company that achieved more than 47M users within around 3 years since its launch in 2018 has hugely diversified employees who are from 40 different countries. The number of employees by now is more than 1,000 staff members, and yet the company is still incomplete and at a growing stage.

To build "PayPay", we allied with Paytm, the biggest payment service company in India. Based on their customer-first technologies , we created and expanded the smartphone payment service in Japan.

Our biggest competitor is "cash". We are seeking for people who can accept this challenge positively, brush up the product at a tremendous speed that other companies could never achieve, and who are passionate about promoting and spreading such a financial life platform in a short time along with professionalism.

About our working style, we had introduced a new personnel system called WFA (Working From Anywhere*). At PayPay, we work fully remotely in Japan. Therefore, the working place or your living place doesn't matter. Even if you are living in a local area, the salary and benefit package will be at an international level while you enjoy working with world class colleagues. You will find such a way of working at PayPay! *This WFA policy is applicable only within Japan.

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

Your qualification

• 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
• English language only is welcome! Japanese bilingual ideal
• 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 (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

Expected personality

• Strong problem-solving and analytical skills
• Excellent communication and collaboration abilities
• Adaptability and a willingness to learn new technologies and techniques
• Proactive mindset with the ability to think strategically about team and company needs
• Ability to make suggestions and improvements independently
• Logical communicator with the ability to coordinate smoothly with stakeholders

Portrait

• Unparalleled speed: Discover for yourself the important things that need to be done and implement ways to reach the best results at the fastest speed possible for the organization
• Commitment: As a professional, commit to the growth and business goals of the organization and create impactful results by your ownership
• Logical thinking: Think logically and structurally to bring real communication
• Curiosity and questioning mind: Keep your curiosity about new things and your challenges along with a continuous questioning mind and enjoy such circumstances in a future-oriented manner
• Problem solving: Take a proper approach towards both explicit and potential business/organization challenges to lead solutions involving others

What we offer

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

Additional details

PayPay 5 senses

• Please refer PayPay 5 senses to learn what we value at work.

Employment Status

• Full Time

Office Location

• WFA(Work From Anywhere at Anytime)
• Remote Job
• You can live anywhere in Japan

Work Hours

• Super Flex Time (No Core Time)
• In principle, 10:00am-6:45pm (actual working hours: 7h45m + 1h break)

Holidays

• Every Sat/Sun/National holidays (In Japan)/New Year's break/Company-designated Special days

Paid leave

• Annual 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.

Salary

• Annual salary paid in 12 installments (monthly)
• Based on skills, experience, and abilities
• Reviewed twice a year
• Special Incentive once a year *Based on company performance and individual contribution and evaluation
• Late overtime allowance, Work from anywhere allowance (JPY100,000)