Description
: Business Overview
Rakuten group has almost 100 million customers in Japan and 1 billion customers around the world, and provides more than 70 services such as e-commerce, payment services, financial services, mobile, media, sports, etc.
Department Overview
AI Services Supervisory Department (AISSD) provides data-oriented solutions by leveraging data science and Rakuten group's data gathered from 70+ services. The department contributes to Rakuten's business units and Rakuten's business partners as well. We have the strategic vision "Rakuten as a data-driven membership company". AISSD has the mission to realize it.
Among the AISSD, the Data Science Consulting Department (DSCD) serves as a bridge between the business units and the development units. We propose data-driven solutions based on a deep understanding of the business and swiftly drives their implementation.
Business domain
Commerce & Marketing:
- Driving data solution of Commerce Company of Rakuten Group (Rakuten Ichiba, Rakuma, Rakuten Fashion, etc.) by maximizing value of data.
- Providing data-oriented solutions utilizing clients and Rakuten data for external customers, such as manufacturers, retailers, and local governments, through marketing actions such as ads and media.
Mandatory Qualifications:
Computer science or related background
5+ years' experience in software development, 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
Experience with SQL and some of the modern relational databases
Desired Qualifications:
Experiences in web service development in multiple industries.
Solid knowledge of large volumes data processing
Experience with Big Data ML toolkits, such as Mahout, SparkML, or H2O
Experience with NoSQL databases, such as HBase, Redis, CouchBase
Familiar with data mining concepts and machine learning algorithms
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
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Languages:
English (Overall - 3 - Advanced)-
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