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

Job Responsibilities

• Own end-to-end design, implementation, evaluation, and maintenance of ML 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 to provide data-driven insights that influence product strategy.
• Collaborate with data engineers, product managers, and stakeholders to build robust production systems.
• Contribute to experimentation design and data-driven insights to drive product improvements.

Technical Stack

Required Skills

• Bachelor's degree in a quantitative field (e.g., CS, ML, Math, Statistics, Economics, Physics)
• 5+ years as a data scientist, ML engineer, or equivalent
• Proficiency in Python and SQL
• English communication (verbal and written); Japanese beneficial for cross-functional collaboration

Preferred Skills

• Master's or PhD in a quantitative field
• 7+ years of experience
• Big Data: BigQuery, Spark, Hadoop, AWS Redshift, Kafka, or Kinesis
• ML/DS domains: recommender systems, deep learning, NLP, optimization, anti-fraud
• AWS: Glue, SageMaker, Athena, S3
• Databricks or Snowflake
• Designing/conducting A/B tests and hypothesis testing
• Building and maintaining microservices
• Japanese language proficiency

Career Growth Perspective

• Opportunity to own the production ML lifecycle end to end, directly impacting PayPay products and data-driven decision-making.
• Exposure to architecture leadership across DS systems, experimentation design, and cross-functional collaboration (data engineering, product, business).
• Experience with large-scale data platforms and cloud/modern data tooling (BigQuery, Spark/Hadoop, Redshift, Kafka/Kinesis, AWS services, Databricks/Snowflake) in a FinTech context, enabling growth in technical breadth and leadership.