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Senior Data Science Engineer / Senior Machine Learning Engineer
- New York, New York, United States
- New York, New York, United States
About
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.
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Languages
- English
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