Data Scientist - Commerce & Marketing Consulting Section, AI & Data Consult at Rakuten

Tokyo, , Japan -

Full Time

Start Date

Immediate

Expiry Date

13 Jan, 26

Salary

0.0

Posted On

15 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Analytics, Machine Learning, Python, SQL, Big Data, Spark, AWS, GCP, Data Visualization, Exploratory Data Analysis, Predictive Models, Collaboration, Communication, Problem Solving, Knowledge Sharing

Industry

Software Development

Description

Job 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 AI & Data Consulting Department (AIDC) 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. Position Details - Work on the full data science process, from initial problem formulation and ideation through to model building and deployment of data science products. - Flexibly utilize Rakuten’s primary big data, as well as relevant third-party data (e.g. offline sales data, geo-spatial data, government statistics, etc.) to uncover trends and patterns that help our business succeed. - Use SQL in a big data context to extract data to support business needs. - Select and implement the most appropriate predictive models and algorithms for the issue at hand. - Focus on building solutions and data products that can be utilized beyond a single-project scope. - Collaborate closely with other data scientists, consultants, project managers and data strategists. - Communicate effectively with stakeholders, both in discussing approaches and in presenting results with appropriate visualizations. - Formulate and propose novel solutions to existing business challenges in a pro-active way. - Keep up with industry trends in data science/machine learning and consider when to introduce them to Rakuten/your projects. - Promote a knowledge sharing and learning culture. 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: - 3+ years of relevant work experience in data science, analytics or related areas. - Solid understanding of foundational statistics concepts and ML algorithms: random forest, gradient boosting machines, neural nets, etc. - Experience building data science solutions for real business problems. (e.g. recommendation building, customer journey definition, shopping feature prediction, etc). - Skilled in self-directed exploratory data analysis. - Fluency in using Python (pandas, scikit-learn or equivalent tools) for data analysis. - Experience with working on large data sets, especially with Spark, and/or cloud platforms such as AWS and GCP. - Ability to extract, combine and analyze complex datasets using SQL. - Ability to work collaboratively in a team environment and work effectively with people at all levels in an organization. - Ability to distill complex data and findings into clear, presentable reports. - Ability to effectively communicate with non-technical as well as technical audiences. Desired Qualifications: - 3+ years of industry experience especially in digital marketing, e-commerce or customer analytics-related fields. - Experience with model deployment and/or working with Data Engineers, Software Engineers, etc. in integrating analysis results and models into production systems. - Experience with data visualization tools #engineer #datascientist #researcher #DataEngineer #AI #aianddatadiv Languages: English (Overall - 3 - Advanced), Japanese (Overall - 3 - Advanced) 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

Responsibilities

Work on the full data science process, from initial problem formulation and ideation through to model building and deployment of data science products. Collaborate closely with other data scientists, consultants, project managers, and data strategists to propose data-driven solutions and drive their implementation.