Job Description: Department Overview The Rakuten AI & Data Division (AIDD) creates powerful, customer-focused search, recommendation, data science, advertising, marketing, pricing, and inventory optimization solutions for various businesses in commerce, fintech, and mobile industries. Rakuten Institute of Technology (RIT), the AI R&D engine of Rakuten Group, is a global network of research labs spanning Tokyo, Singapore, Boston, San Mateo, Bengaluru, and Paris. We are dedicated to pioneering advancements in core AI technologies, with a focus on machine learning, deep learning, and generative AI. Our researchers are actively exploring the use case of large language models, intelligent agent systems, and other cutting-edge applications, driving innovation across Rakuten's diverse ecosystem. Fintech AI is one of the research topics at RIT and is positioned as a critical research area within the Rakuten Group, particularly in its FinTech businesses. Research scientists develop algorithms related to credit scoring, risk scoring, and customer credit evaluation. As a Research Scientist, you will work on developing new credit models and improving existing ones by analyzing various types of data, such as customer attributes, behavioral data, and delinquency data, as well as through discussions with business stakeholders. When releasing new models, research scientists are responsible for conducting offline evaluations using historical data and designing online proof-of-concept (POC) experiments. The role of a research scientist requires the following: (1) Understanding business challenges and providing appropriate solutions to contribute to improved business performance. (2) Identifying promising research from the latest studies that could benefit the business in the long term and applying it to real-world environments. For this particular position, we are seeking Research Scientists who can apply their expertise in one or more of the following areas to real-world business scenarios: - Building embeddings using Deep Learning - Multi-task Learning/Transfer Learning - Causal Inference Additionally, to achieve the goals outlined in (1) and (2), research scientists are expected to adopt a hypothesis-driven approach, which may involve conducting ad-hoc data analyses repeatedly as needed. Position: Why We Hire Fintech AI group is seeking research scientists with a background in data analysis, algorithm design, and implementation, who can work together on the above research topics. Position Details - Define short/middle-term direction of projects while aligning with business, product and engineering team - Design algorithms to solve defined research problems. Also, appropriately implement the designed algorithms and evaluate their performance - Work with Project Management team to gather business requirements, define suitable KPIs and validate if the solutions meets/exceeds the requirements/KPIs - Support engineering teams and product teams to adapt prototypes in production - Support junior-level research scientists - Contribute to the advancement of science via writing papers, attending conferences, submitting patent proposals and verifying the feasibility in the business applications Mandatory Qualifications: - Ph.D. in Computer Science or a related field, or equivalent practical experience - Ability to effectively communicate with research scientists, engineers, and business personnel in English - Ability to work independently and drive projects forward - Proficiency to analyze data and build ML/AI model using Python - Basic understanding of statistics, machine learning and deep learning with some practical experience - Development experience in a Unix/Linux environment - Proficient in code management (e.g., Git) - Interest and curiosity about user behavior and credit scoring Desired Qualifications: - Strong international publication records - Demonstrated project achievements, such as GitHub repositories - Experience leading research members for more than two years - Ability to effectively communicate with business personnel in Japanese - Knowledge in at least one of the following areas: ・Building embeddings using Deep Learning ・Multi-task Learning/Transfer Learning ・Causal Inference Other Information: Additional information on English Qualification English (Overall - 4 - Fluent) #engineer #datascientist #researcher #technologyservicediv #Python In Japanese, Rakuten stands for ‘optimism.’ It means we believe in the future. It’s an understanding that, with the right mind-set, we can make the future better by what we do today. So we challenge ourselves to evolve, innovate and experiment, to create a better, brighter future for everyone. Today, our 70+ businesses span e-commerce, digital content, communications and fintech, bringing the joy of discovery to almost 1.3 billion members across the world. If you have any trouble logging in, please contact us here Rakuten Group, Inc.: rakuten-recruiting-info@mail.rakuten.com Please read the Application Requirements(EN) / 募集要項(JP) before applying. Our Diversity & Inclusion Policy and Application Documents Rakuten’s corporate mission is to “contribute to society by creating value through innovation and entrepreneurship.” We foster a culture that provides equal opportunities to those who share this founding philosophy and take on the challenge to transform society, regardless of age, gender, nationality, or any other status. Diversity is one of Rakuten's core strategies and a driving force for innovation. Because of this, you are not required to submit any of the following information in order to apply for our job positions. - Gender - Age - Photo - Nationality - Information not related to business, such as ideological beliefs, family structure, etc. * For legal compliance, we may ask you about your work eligibility. See the details