Senior Data Scientist, Credit Modeling

About PayPay

PayPay is a FinTech company that has grown to over 70M (as of July 2025) users since its launch in 2018. Our team is hugely diverse with members from over 50 different countries.

OUR VISION IS UNLIMITED_

We dare to believe that we do not need a clear vision to create a future beyond our imagination. PayPay will always stay true to our roots and realize a vision (future) that no one else can imagine by constantly taking risks and challenging ourselves. With this mindset, you will be presented with new and exciting opportunities on a daily basis and have the opportunity to grow and reach new dimensions that you could never have imagined. We are looking for people who can embrace this challenge, refresh the product at breakneck speed and promote PayPay with professionalism and passion.

※ Please note that you cannot apply or be selected in parallel with PayPay Corporation, PayPay Card Corporation and PayPay Securities Corporation.

Job Description

We are looking for a leader with a passion to develop novel machine learning software systems for credit modeling and default risk prediction, deploy the systems to production, and test them to ensure all users and merchants needs are covered.

You will perform ETL to build model features using petabyte-scale datasets and develop high throughput and low latency systems to serve models in production touching the lives of more than 65 million customers every day. You will collaborate with highly innovative engineering teams to put machine learning functionalities into production systems that we build in-house.

We are looking for someone who oozes passion, ownership, and a love of building great things. The Product and Engineering teams will rely heavily on your build. You'll have a ton of trust and responsibility. So, if challenges excite you, and you're ready for a big one, let us know.

Responsibilities

• Drive a roadmap that applies Machine Learning technologies to content discovery, engagement, recommendation, predication, risk underwriting etc.
• Work with the leadership team to identify opportunities for using ML and drive solutioning in areas of Credit
• Work with stakeholders to show them the benefits of using your system and driving adoption of the product
• Designing scalable and deployable machine learning solutions
• Define performance and validation metrics and coach the team to achieve these
• Introduce and own the process of model building and the infrastructure behind it

Qualifications

• 8+ years of software engineering experience and a proven track record of successfully architecting and taking ML systems to production.
• Designed and built multiple complex, scalable, high throughput, low latency streaming/batch processing machine learning pipelines for both data flows and algorithm execution
• Ability to explain and present analyses and machine learning concepts to a broad technical audience
• Have an extreme bias towards action. Basically, have the “Get Things Done” type of attitude.
• Be able to maintain high-performance within a high-energy and fast-paced work environment.
• You have a master degree or equivalent in Computer Science, Engineering, Mathematics or related field
• Working knowledge of PyTorch, Tensorflow or other similar frameworks is a plus
• Working experience of AWS SageMaker, Google Vertex is a plus

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

PayPay 5 senses

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

Working Conditions 

Employment Status

• Full Time

Office Location

• Hybrid Workstyle (flexible working style including Remote and office)
  ※There are no fixed rules regarding office attendance in Product group; it depends on each individual's discretion.
• LIFE in JAPAN FACTBOOK

Work Hours

• Super Flex Time (No Core Time)
• In principle, 9:00am-5:45pm (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 once a year
• Special Incentive once a year *Based on company performance and individual contribution and evaluation
• Late overtime allowance
  
  ※Payroll payment can be changed to digital salary payment “PayPay Paycheck” for an amount set by you

Benefits

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

Other Information:

• PayPay Inside-Out (Corporate Blog) /JP
• PayPay Inside-out (Corporate Blog) /ENG
• PayPay Product Blog /JP
• PayPay Product Blog /ENG