Research Scientist, Customer Program - Rakuten Institute of Technology Tokyo (RIT)

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Rakuten is the one of the largest internet services company globally and provides more than 70 services spanning eCommerce, finance, telecommunication, sports and much more to approx. 1.4 billion customers worldwide. Following the strategic vision “Rakuten as a data-driven membership company”, we are expanding our data activities across our multiple Rakuten group companies.

Department Overview

The Customer Program, one of our core sciences programs, builds models for customer understanding and applying them to customer targeting solutions. We are working on the following research topics in the Customer Program at our Tokyo office:

Credit Scoring: It is one of crucial research topics across Rakuten Group (Mainly in our fintech businesses such as credit card, payment, securities and banking business). Research scientist applies machine learning, data mining and optimization techniques to solve challenging problems, build models and solutions regarding credit scoring related projects. Our solution includes scoring for both business clients and individual users.

Social Graph: Rakuten has already been applying various kinds of marketing measures based on customer profiling, target prospecting algorithms. Those models were built with individual customer behavior data. However, if we aware of social relationship between Rakuten members, such as family, colleges, friends, it is possible to improve performance of the marketing measures. With this assumption, research scientists builds the social graph structure among Rakuten members and their relatives by collecting data from multiple Rakuten services, and apply graph algorithms including graph neural networks to conduct marketing measures, such as family introduction campaign, based on the social graph.

Geo Science: With more than 70 different services in the Rakuten Group globally, our data science teams cover diverse initiatives in both the online and offline worlds. Offline Geo data and Geo Science applications are key to the optimization and overall success in fields including Logistics, Site Planning, Area Marketing and improving Customer Experience. The Geo Science Team creates algorithms and builds new Geo Intelligence layers to better understand offline activity to support many Rakuten Group services.

Marketing Optimization: Rakuten group is contacting to our customers with various kinds of communication channels such as showing banners on web pages, sending email, pushing notifications through apps to promote our products and services. To deliver right contents at the right time to the right customers, research scientist applies various kinds of machine learning algorithms such as reinforcement learning, deep learning to build models to marketing platforms.

Federated Learning: Rakuten group is conglomerate. As each group company has its own privacy policy, detailed user behavior data cannot be shared with each other even if they are within Rakuten Group. Federated learning scheme is required in order to build customer models with fully utilizing Rakuten group data and complying privacy policies.<

We are looking for research scientists with a strong research background in user behavior, machine learning, and a strong desire to join our team.

Position:

Why We Hire

We are looking for talented research scientists with a strong research background in at least one of the related fields (user behavior, AI for marketing, AI for fintech, geo-spatial data or advanced algorithm development) and a strong motivation to join an exciting team that is constantly evolving and pushing the envelope on AI and its applications.

Position Details

• Work on research projects with senior members
• Develop state-of-the-art algorithms and implement prototypes while working with senior members
• Join the discussion on short/middle-term direction of projects while communicating with business, product and engineering team
• Work with Project Management team to gather business requirements, set evaluation metrics and calculate if the solution meets/exceeds them
• Support engineering teams and product teams to adapt prototypes in production
• Contribute to the advancement of science via writing papers, attending conferences and submitting patent proposals

Mandatory Qualifications:

• Master degree in computer science, mathematics, physics, econometrics or equivalent practical experience
• Publication record in area of machine learning, data mining and related research fields or have experience of productizing research outcomes in an industry
• English fluency and ability to communicate effectively with researchers, engineers, and business people
• Strong programming experience in one or more of the following: Python, R, Scala, Java, C, C++
• Self-motivated and willingness to take challenges to new technologies, research problems and services

Desired Qualifications:

• Doctoral degree in computer science, mathematics, physics, econometrics or equivalent practical experience
• Passion for contributing to businesses by applying innovative solutions to real world problems
• Development experience in Unix/Linux
• Experience in distributed computing such as Spark and Hadoop