Rakuten

Data Science Engineer, Fraud Prevention Section - Membership Platform Department (MPD)

Tokyo, Japan
Machine Learning Python Hadoop AWS Docker Spark SQL Azure GCP Kubernetes
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Description

Job Description:

Business Overview

The Technology Platforms Division (TPD) is responsible for building and operating the infrastructure and ecosystem platforms which power the Rakuten Group. Our mission is to provide our Rakuten Cloud and Ecosystem Platforms which will deliver Core Value to accelerate the growth of Rakuten Group services.

Department Overview

The Membership Platform Department (MPD) is thinking big: we create scalable platforms that power the Rakuten Ecosystem worldwide. Are you interested in building the next generation of Internet services that reach hundreds of millions of users across the globe every day? In our department, you will join a global team of experienced technologists who build the foundation of our services.

The Fraud Prevention Section is a diverse team with members from all over the world. We protect Rakuten Businesses and Members by investigating fraud, and developing high-performing fraud prevention solutions capable of processing high volumes of transactions in real-time. Attack methods are always evolving and so we welcome innovative ideas and value people who take an interest in the latest technology, and share the mindset of protecting our users.

Overall Position Details

As a Data Science Engineer, this role will require you to:

- Work on Machine Learning model training for diverse type of businesses.

- Be hands-on, starting from participation with business units (BUs).

- Understand the problem statement and set technical requirements.

- Train models and explain the results.

- Deploy the model to production to achieve impact.

Mandatory Qualifications

- Bachelor's degree or above in computer science, Information Systems, or a related field.

- Strong understanding in data engineering, including designing and building data pipelines and data integration solutions.

- Strong understanding of SQL and NoSQL databases, data warehousing concepts, and data modeling techniques.

- Familiar with data mining concepts and machine learning algorithms

- 5+ years experience in Machine Learning Modelling, especially using Python as a programming language

- Experience with common Linux commands and Linux scripting languages

- Experience with Hadoop, MapReduce, HDFS and Big Data querying tools, such as Tez, Hive, and Impala

- Experience with designing and building tools based on specific requirements

- Experience with building and maintaining data science platform

Desired Qualifications:

- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and related data services.

- Experience of cloud technologies, including Docker and Kubernetes

- Experience with Spark and stream-processing systems, using solutions such as Storm or Spark-Streaming

- Knowledge of various ETL techniques and frameworks, such as Flume etc.

Other Details

- Work Location: Tokyo

Languages:

English (Overall - 4 - Fluent)

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