PayPay
Senior Data Science Engineer - Data Insights
Job Summary
This role involves processing, analyzing, and visualizing both structured and unstructured data, and designing algorithms for predictive modeling and recommendations. Collaboration with data engineers, product managers, and stakeholders is essential to build robust production systems. Candidates should have a background in quantitative fields, extensive experience in data science or software engineering, and proficiency in programming languages like Python, Java, or Scala, as well as SQL. The position offers a hybrid work environment, flexible hours, comprehensive benefits, and opportunities to work with advanced technologies such as big data tools, machine learning, and recommendation systems.
Required Skills
Benefits
Job Description
About PayPay
PayPay is a FinTech company that has grown to over 69M (as of May 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
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 for the Data Insights department.
Team Missions
- To drive value-added product improvements by engineering systems founded on a scientific understanding of user and merchant behavior
- Our scope of work spans engineering, product science, data science, machine learning, statistical inference, optimization, and BI analytics
Responsibilities
- Process, analyze, and create visualizations for both structured and unstructured data
- Design and maintain algorithms for predictive modeling and recommendations
- Collaborate with data engineers, product managers, and stakeholders to build robust production systems
Required Qualifications
- Bachelors in a quantitative field such as Computer Science, Mathematics, Statistics, Machine Learning, or equivalent
- Excellent verbal and written communication skills in English and/or Japanese
- More than five years of work experience as a data scientist, software engineer, statistician, or equivalent role
- Experience in at least one primary language (e.g., Java, Scala, Python) and SQL (any variant)
Preferred Qualifications
- Masters or PhD in a quantitative field such as Computer Science, Mathematics, Statistics, Operations Research, Machine Learning, or equivalent
- More than seven years of experience as a data scientist, machine learning engineer, or equivalent role
- Experience building and maintaining microservices
- Experience with Big Data technologies like BigQuery, Spark, Hadoop, AWS Redshift, Kafka, or Kinesis streaming
- Extensive knowledge and work experience in recommendation systems, deep learning, NLP, and optimization
- Experience with AWS services such as Glue, SageMaker, Athena, and S3
- Experience designing and conducting A/B and hypothesis tests
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 + 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
- 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
- Language Learning support
- Translation/Interpretation support
- VISA sponsor + Relocation support
PayPay
PayPay is an app that lets you make easy and convenient payments with just your smartphone. Registration is complete in as little as one minute! You can use it at stores, for online services, and to pay bills.
See more jobsSafe Remote Job Search Tips
Verify Employer Thoroughly
Research the company's identity thoroughly before applying. Check for a professional website with contacts, active social media, and LinkedIn profiles. Verify details across platforms and look for reviews on Glassdoor or Trustpilot to confirm legitimacy.
Never Pay to Get a Job
Legitimate employers never require payment for applications, training, background checks, or equipment. Always reject upfront payment requests or demands for bank details, even if they claim it's for purchasing necessary work gear on your behalf.
Safeguard Your Personal Information
Protect sensitive data like SSN, bank details, or ID copies. Share this only after accepting a formal, written job offer. Ensure it's submitted via a secure company system or portal, never through insecure channels like standard email attachments.
Scrutinize Communication & Interviews
Watch for communication red flags: poor grammar, generic emails (@gmail), vague details, or undue pressure. Be highly suspicious of interviews held only via text or chat apps; legitimate companies typically use video or phone calls.
Beware of Unrealistic Offers
If an offer's salary or benefits seem unrealistically high for the work involved, be cautious. Research standard pay for similar roles. Offers that appear 'too good to be true' are often scams designed to lure you into providing information or payment.
Insist on a Formal Contract
Always secure and review a formal, written job offer or employment contract before starting work or sharing final personal details. Ensure it clearly defines your role, compensation, key terms, and conditions to avoid misunderstandings or scams.