CAREERS

The Senior Research Scientist for Theoretical Physics is responsible for the building of new research prototypes from scratch for their eventual productionization and for publishing new ideas in top research conferences. This role is part of the global Rakuten Institute of Technology (RIT), the corporate R&D department responsible for leading strategic technological progress. RIT collaborates with the Harvard Quantum Initiative to accelerate the application of quantum technology to industry, and as the part of this collaboration, the researchers will have the access to Harvard Department of Physics facilities as visiting scholars.

The Vision Program, which is one of our core science programs, aims to process and understand images and videos using advanced computer vision and machine learning. We are working in areas such as estimating product attributes for large-scale image datasets for creating catalogs, robust document image understanding for smooth customer onboarding, image generation and enhancement for attractive, personalized recommendations, and other applications to handle the large amount of visual data in Rakuten’s businesses. We are interested in leveraging weakly-, semi-, and unsupervised techniques to reduce labeling costs as well as techniques to increase efficiency during model training and deployment.

The Vision Program is looking for a research scientist with strong research background in the field of computer vision & machine learning and motivation to join our team.

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.

Fintech Optimization: Rakuten Securities is one of the top asset management platforms in Japan. Our scientists work closely with foreign exchange dealers and stock traders from Rakuten Securities to develop algorithms that competitively price assets based on real-time customer transactions and market conditions. We are working on challenging problems including pricing and user demand forecasting, and pricing optimization for services including foreign exchange and stock lending, using various machine learning algorithms.

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

The Language program, which is one of our core science programs, aims to automatically create a well-organized product catalog using advanced NLP and ML technologies to generate structured information from unstructured product titles, descriptions, and images. We are also interested in leveraging weakly/semi-supervised and unsupervised techniques to incorporate signals beyond traditional sources, such as customer behavior data, to augment our language understanding. We are looking for research scientists with a strong research background in the NLP field and strong motivation to join the Language program.