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Senior Data Scientist - Financial Service Development Section

📁
R&D Scientist
💼
Rakuten, Inc.
📅
00008446 Requisition #

Rakuten is one of the leading e-commerce companies in the world.

Our mission is to empower people and society through the internet while aiming at becoming the Global Innovation Company.

 

Financial Service Development Section is the tech team that develops various services for Fintech Business in Rakuten Group. As a Data Scientist, you will mainly work on managing huge scale, high availability and real time processing of Big Data, and provide the models and algorithms like credibility model based on machine learning. 

 

Responsibilities:

  • Utilizing the big data to identify the problems and analyze the solutions
  • Develop the models and algorithms based on the both hypothesis drive analysis and data mining analysis
  • Implement data-driven scalable solutions with technology that actually functions in the service by collaborating with software engineers
  • Manage the requirement and quality of project and product by working with project/product managers
  • Consulting and delivery support for application of our products
  • Managing the team members and build the good collaboration with the stakeholders
  • Expanding the capability of the data science team in the company

Minimum Qualifications:

  • 5+ years' experience in analyzing heterogeneous data in real world using machine learning
  • Proven knowledge in machine-learning-based data analytics
  • 5+ years' experience in machine-learning-based data analytics
  • Proven background in applied mathematics (statistics, optimization, machine learning, graph theory, algebra, etc.)
  • 5+ years' experience in developing products with multiple modern programming languages
  • Solid technical knowledge on data platform for big data like Oracle, Teradata, etc.
  • Proven experience in using big data platform like Hadoop (Hive, MapReduce, etc.)
  • Willingness and skills to learn new technologies / programming languages by yourself when they are necessary
  • Skills to develop the best solutions with machine learning and mathematical methodology to the existent problems by understanding business requirements

 

Preferred Qualifications:

  • Experience publishing academic papers for international academic conferences (SIG-KDD, ICML, ICDM, etc.)
  • Experience participating in international academic conferences as a speaker
  • Experience in joining data science competitions, such as Kaggle and being in a good rank
  • Skills to work in a team-oriented environment
  • Knowledge and experience on analyzing data that is difficult to handle due to its peculiarity
  • Experience with Big Data ML toolkits, such as Mahout, SparkML, or H2O
  • Experience building stream-processing systems, using technologies such as Kafka, Storm and Spark-Streaming
  • Experience with NoSQL databases, such as HBase, Redis, CouchBase, Cassandra, etc. and NewSQL databases like Google Spanner, CockroachDB, etc.
  • Analysis and BI skills to identify meaningful patterns, analyze them, and integrate them through visualization as well as business communication skills for understanding real requirements from users

Education:
  • MS degree in a mathematics (statistics, optimization, machine learning, graph theory, algebra, etc.)

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