Rakuten group has almost 100 million customer bases in Japan and 1 billion globally as well, providing more than 70 services in a variety such as ecommerce, payment services, financial services, telecommunication, media, sports, etc.
Following the strategic vision “Rakuten as a data-driven membership company”, we are expanding our data activities across the Rakuten Group. We are looking for Data Scientists to support this direction within the AI Success Supervisory Department.
In this department, data scientists mainly utilize customer data gathered from services such as Rakuten Ichiba, Rakuten Mobile, etc., to derive insights and build data science solutions. These solutions are designed to support not just Rakuten itself, but also to empower our merchants and business partners towards greater success. Topic areas can be very broad, but mostly focus on using transactional, behavioral and demographic data to drive customer acquisition, customer retention and business process improvement (e.g. data-driven labor/cost-reduction, media spend optimization, etc.).
- 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.
- 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.
- 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.
- Communication skill in both English and Japanese
- Experience with data visualization tools
|Location||Rakuten Crimson House, 1-14-1 Tamagawa, Setagaya-ku, Tokyo158-0094
(1 min walk from Futakotamagawa Station on the Denentoshi Line)
|Remote work||Partial remote|
|Working hours||9:00am - 5:30pm (Every Monday, work hours are from 8:00am to 4:30pm due to morning meeting)|
|Holidays||・2 days off per week (Saturdays, Sundays, and national holidays are holidays)
・10-20 days of annual paid vacation (the minimum number of days is the number of days granted after six months of employment)
・120 days off per year
In addition, year-end and New Year vacations, paid vacation, congratulation or condolence leave, maternity and paternity leave, etc.
*Once a year, you can take 9 to 12 consecutive holidays by using the long vacation (Success Vacation) system.
|Employee benefits||・Commuting allowance
・Employee pension insurance
・Workers' accident compensation insurance
・Retirement allowance system
Supplemental education and qualification support
・English learning support (in-house TOEIC(R) test IP test, English conversation, etc.)
・Career challenge system (challenge the department of your choice)
・Job return system (rehiring system for those who retired due to marriage, childbirth, nursing care, etc.), etc.
・Stock Option Plan
・Cafeteria system with three free meals
・LILO Club (preferential treatment at sports clubs, accommodations, leisure facilities, movie theaters, etc.)
・LILO Club (sports clubs, lodging, leisure facilities, movie theaters, etc.) (Running, mountain climbing, cooking, etc., part of the expenses paid by the company)
・Free English conversation lessons by native English speakers
・Support system for certification acquisition
・Qualification support system, etc.
|Others||- Your application will be reviewed by multiple departments.
- You may have several interview processes by multiple departments in parallel.