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 or Senior Machine Learning Engineer for the Data 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
Required Qualifications
• 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