Senior Data Science Engineer / Senior Machine Learning Engineer (Applied Insights)

About PayPay

PayPay, a FinTech company that has achieved more than 75M (as of August 2026) since its launch in 2018, is rapidly expanding its business scale as a payment platform used by approximately one out of every two smartphone users in Japan.

The company has a diverse team of professionals from more than 50 countries and is building a world-class engineering organization.

Our biggest competitor is "cash". They are seeking people who can accept this challenge positively, brush up on 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.

PayPay is committed to maintaining a "Day 1" mindset, bringing to life visions of the future that no one else can even imagine. At PayPay, we provide an environment where everyone can deliver outstanding performance as professionals, through a flexible work style that includes remote and office.

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Position

PayPay's growth is driving a rapid expansion of PayPay product teams, and the need for a robust data platform that drives cutting-edge data science and powers machine learning innovations is more critical than ever in order to support our growing business needs. We are looking for a Senior Data Science Engineer or Senior Machine Learning Engineer for the Applied Insights department.

Team Missions

• The team's primary focus is building and deploying models that directly power PayPay products, with secondary responsibility for experimentation and data-driven insights.
• The team drives product improvements by engineering systems founded on a scientific understanding of user and merchant behavior.
• The scope of work spans engineering, product science, data science, machine learning, statistical inference, optimization, and BI analytics.

Responsibilities

• Own end-to-end design, implementation, evaluation, and maintenance of machine learning models for prediction, recommendation, anti-fraud, etc. from problem framing to production
• Lead architectural decisions for data science systems. Process, analyze, and visualize user and merchant data, providing data-driven insights that influence product strategy for technical and business divisions.
• Collaborate with data engineers, product managers, and stakeholders to build robust production systems

Your qualification

• Bachelors in a quantitative field such as Computer Science, Machine Learning, Mathematics, Statistics, Economics, Physics, or equivalent
• Verbal and written communication skills in English. English is the primary working language for the team; Japanese is beneficial for cross-functional collaboration.
• More than five years of work experience as a data scientist, machine learning engineer, or equivalent role
• Experience in Python and SQL (any variant)

Preferred Qualifications

• Masters or PhD in a quantitative field such as Computer Science, Machine Learning, Mathematics, Statistics, Economics, Physics, or equivalent
• More than seven years of experience as a data scientist, machine learning engineer, or equivalent role
• Experience with Big Data technologies like BigQuery, Spark, Hadoop, AWS Redshift, Kafka, or Kinesis streaming
• Experience with recommendation systems, deep learning, NLP, optimization, or anti-fraud systems
• Experience with AWS services such as Glue, SageMaker, Athena, and S3
• Experience with Databricks or Snowflake
• Experience designing and conducting A/B and hypothesis tests
• Experience building and maintaining microservices
• Verbal and written communication skills in Japanese

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.

Working Conditions 

Employment Status

• Full Time

Office Location

• Hybrid Workstyle

*You will be expected to work in the office, in alignment with organizational guidelines and team objectives.

• LIFE in JAPAN FACTBOOK

Work Hours

• Super Flex Time (No Core Time)
• In principle, 9:00am-5:45pm + 1h break (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
• Late overtime allowance

*Payroll payment can be changed to digital salary payment “PayPay Paycheck” for an amount set by you