About PayPay
PayPay is a fintech company that has grown to over 58M users since its launch in 2018. Our team is hugely diverse with members from over 50 different countries. To build "PayPay", we allied with Paytm; the biggest payment service company in India. Based on their customer-first technology, we created and expanded the smartphone payment service in Japan.Our biggest competitor is "cash". We seek people who can accept this challenge positively, brush up the product at a tremendous speed, and promote PayPay with professionalism and passion.
Team Missions
- To drive 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
- Drive product innovations and improvements with scientific research and analysis
- Conduct experiments and hypothesis testing to understand user and merchant behavior
- Measure and monitor product KPIs to identify product opportunities and successes
- Process, analyze, and create visualizations for both structured and unstructured data
- Collaborate with engineers, product managers, designers, and stakeholders to quickly iterate the product development cycle
Required Qualifications
- Bachelors in a quantitative field such as Computer Science, Mathematics, Statistics, Machine Learning, or equivalent
- Solid background in experimental design, data analytics, and scientific research
- Excellent verbal and written communication skills in English and/or Japanese
- More than three years of experience as a data scientist, product scientist, machine learning engineer, or equivalent role
- Proficiency in at least one primary language (e.g., Java, Scala, Python) and SQL (any variant)
- Experience working effectively with cross-functional teams
Preferred Qualifications
- Masters or PhD in a quantitative field such as Computer Science, Mathematics, Statistics, Operations Research, Machine Learning, or equivalent
- More than five years of experience as a data scientist, product scientist, machine learning engineer, or equivalent role
- Experience with Big Data technologies like BigQuery, Spark, Hadoop, AWS Redshift, Kafka, or Kinesis streaming
- Experience with AWS services such as Glue, SageMaker, Athena, and S3
- A track record of working in a fast-paced environment and dealing with ambiguous requirements
- Experience designing experiments with causal inference
PayPay 5 senses
Working Conditions
Employment Status
Office Location
Work Hours
- Super Flex Time (No Core Time)
- In principle, 10:00am-6:45pm (actual working hours: 7h45m + 1h break)
Holidays
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)
Benefits
- Social Insurance (health insurance, employee pension, employment insurance and compensation insurance)
- 401K
- Language Learning support
- Translation/Interpretation support
- VISA sponsor + Relocation support
Tags
AWS
big data
data science
hadoop
java
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