Senior Data Science Engineer​/Senior Machine Learning Engineer

Job Description

Pay Pay's growth is driving a rapid expansion of Pay Pay 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.

• The team's primary focus is building and deploying models that directly power Pay Pay 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.

• 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.

• 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).

• 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 Big Query, 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, Sage Maker, 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.