Rakuten is the leading destination for ecommerce and digital life in Japan. It operates over 70 business scenarios including online shopping, fintech, payments, mobile and more. Our mission is to empowering people and society through innovation and entrepreneurship. Rakuten has global offices including Japan, India, China, Singapore, the Europe and the US.
The Rakuten Technology Service Division, creates powerful, customer-focused search, recommendation, data science, advertising, marketing, price and inventory optimization solutions to a variety of businesses in commerce, fintech and mobile industries. We design, develop, and deploy high performance, fault-tolerant distributed systems used by millions of Rakuten customers every day. We strive to deliver the most innovative solutions that are helpful to people and societies around the world.
Why We Hire
We are looking for an exceptional leader who is responsible for creating metrics that best approximate the user values, defining measurement methodology and pipeline, forecasting usage volume, and analysing the data for user insights. The role partners with internal and external teams to pioneering proper scientific use of data in launch decisions and that we are properly optimizing all trade-offs in product design. The role will also incubate new modelling techniques and advocate new tools. The role is expected to lead team to cover full spectrum of measurement, exploration and recommendation for search, recommendation, and ads product.
• Design, size, and analyse field experiments at scale.
• Create novel and tractable datasets from big data.
• Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
• Analyse historical data to identify trends and support decision making
• Provide requirements to develop analytic capabilities, platforms, and pipelines.
• Formalize assumptions about how Rakuten search, recommendation and Ads are expected to work, create statistical definition of the outlier, and develop methods to systematically identify these outliers. Work out why such examples are outliers and define if any actions needed.
• Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.
• Build decision-making models and propose solution for the business problem you defined
• Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.
• Utilize code (python or another object-oriented language) for data analysing and modelling algorithm
• Influence key decisions on launches related to search, recommendation, and Ads product
• Understand the meanings of data and identify specific and actionable opportunities to solve existing business and product problems in search, recommendation, and ads product, and collaborate with engineering, research, and business teams for future innovation
• Build and grow a team of exceptional data scientist and data analyst and program manager (10 subordinates)
• Statistics, Applied Mathematics, Operation Research, Economics or a related quantitative bachelor or master's degree.
• Advanced user of data extraction and transformation tools (e.g Spark, python, SQL)
• Experience designing experiments, ab test, and ability to infer causal relationships
• Demonstrated experience leading a small to medium size team managing data scientist with an eye to driving efficiency]
• Excellent verbal and written communication skills with the ability to effectively advocate data insight to research scientists, engineering teams and business audiences
• Previous experience partnering with cross-functional team across a globally distributed organization and exercising sound judgment
• Experience in e-commerce or with search engines is a plus
|Location||Rakuten Crimson House, 1-14-1 Tamagawa, Setagaya-ku, Tokyo158-0094
(1 min walk from Futakotamagawa Station on the Denentoshi Line)
|Remote work||No 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.