Data Scientist - Project Promotion Department, System Division, Rakuten Card Co., Ltd.
Taihaku Sky Square, Japan
Rakuten
楽天グループ株式会社のコーポレートサイトです。企業情報や投資家情報、プレスリリース、サステナビリティ情報、採用情報などを掲載しています。楽天グループは、イノベーションを通じて、人々と社会をエンパワーメントすることを目指しています。Job Description:
Business Overview
Payment systems, including credit cards, electronic money, and web/app-based payment systems, have become an integral part of our daily lives. Rakuten Card boasts over 30 million issued cards and has achieved the No.1 position in Japan for credit card shopping transaction volume (self-issued basis)*1. Even as an industry leader, we continue to grow without slowing down, aiming for the ambitious "Triple 3" goals: 30 million issued credit cards, 30 trillion yen in shopping transaction volume, and a 30% market share in the credit card industry.
*1 Based on shopping transaction volume of self-issued credit cards in Japan for FY2023, according to Yano Research Institute Ltd. (as of November 2024).
This research result is an estimate based on qualitative research and analysis methods.
Department Overview
Our system department handles all systems supporting Rakuten Card's service lineup, including responding to the rapidly increasing number of members and transaction volumes, as well as enhancing the functionality of Rakuten e-NAVI and the Rakuten Card app. The scope of responsibility spans payment systems, debt management systems, Rakuten e-NAVI, the Rakuten Card app, and call center systems.
Working with us provides the opportunity to engage in cutting-edge technology from the upstream stages, offering engineers a highly stimulating experience.
Why We Hire
Rakuten Card is seeking data engineers to support new improvements and projects aimed at unlocking the value of existing data as part of our efforts to achieve the "Triple 3" goals. Our team aims to leverage data for all Rakuten Card services.
We focus on building data infrastructure, organizing various data, providing data to different business units, and promoting data utilization for all Rakuten Card services.
Responsibilities:
Build data pipelines and data warehouses, as well as provide integrated analytics environments, including BI tools.
Define data collection requirements in collaboration with business teams and create new revenue-generating services using data.
Work Environment:
Mid-career hires: 60%
New graduates: 40%
Backgrounds: SIers, web-based system development companies, etc.
OS: Linux, RHEL, Ubuntu
Mandatory Qualifications
- Business-level communication skills in Japanese or English Knowledge of computer science or related fields
- Basic understanding of statistics
- Ability to work independently and collaborate with international colleagues
- Software development experience, particularly in Python and Java
- Experience implementing machine learning frameworks such as TensorFlow, scikit-learn, PyTorch, or Keras
- Basic knowledge and operational skills in Linux
- Knowledge of SQL and relational databases
Desired Qualifications
- Knowledge of data science methods such as regression, decision trees, and clustering
- Experience in natural language processing using neural networks
- Experience managing and operating big data using tools like Spark, Parquet, Hive, Impala, or Kafka
- Experience designing, developing, and operating AI infrastructure using cloud or Kubernetes
- Experience analyzing data using data warehouses or BI systems
- Practical experience in developing and operating business systems involving large-scale data and transactions
Additional Information About the Location
Fukuoka Office
Additional information on Secondment
You will be employed by Rakuten Group, Inc. and seconded to Rakuten Card Co., Ltd.
※For more information, please refer to the links below:
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▼About Company
・Rakuten Group as a Global Company
▼ Latest Company News
▼ Video Links
・Other Rakuten Group Activities
▼ Conditions of Employment
・Rakuten Group Employee Benefits
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#engineer #datascientist #fintechgroup #RakutenCard
Languages:
Japanese (Overall - 1 - Beginner)* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Big Data Clustering Computer Science Data pipelines Java Kafka Keras Kubernetes Linux Machine Learning ML infrastructure NLP Parquet Pipelines Python PyTorch RDBMS Research Scikit-learn Spark SQL Statistics TensorFlow
Perks/benefits: Career development Team events
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