Data Scientist for Insight - Data Intelligence Supervisory Department
Data Intelligence Supervisory Department is established to create innovation with data across Rakuten group companies.
Rakuten group now provides diverse services that touches every aspect of customers' life including E-commerce (shopping/Ichiba&ebates, travel, golf/GORA, wedding, dining etc), fintech (card, bank, insurance, security etc), media (e-book/Kobo, movie/Viki, cooking-recipe, marriage/o-net etc) and communications (Rakuten mobile, communication app/viber). We are also rapidly expanding our services globally, with our company vision being "global innovation company." All of these services are now being integrated under Rauten brand and membership ID, and thus giving us the opportunity to serve customers better experiences from wholistic poinf of view. "Rakuten as membership company with data" is the strategic vision of Rakuten group, where integrated data can provide deep understanding of customers' contextual needs and demands. By matching with services and products, we are aiming to provide superior personalized experience across Rakuten group.
DISD's vision is to "maximize personal value with data." In order to achieve it, we set the mission as follows;
1. We discover what customers truly want through data
Insight analysis to understand customers' contextual demand and needs.
Figure out what personalization axis (price, gender, age, point sensitivity) is appropriate for a given function (event page, search, category page, ranking page etc)
Build the product asset of customer understanding such as customer DNA
2. We empower makers of services and products to create diversified values of customers
Empower merchants with data science solutions for marketing such as pricing, product line-up, web-page creation or advertisements
Support National clients for understanding of their customers or optimizing their digital advertisements
3. We provide the best match between customers and services/products
Solution development for recommendatoin engine, coupon optimization, search algorithm improvements, advertisement purchase optimization, prediction models of customer attributes etc.
4. We make revenue as the result of creating large impacts to society
5. We create SHIKUMI to scale our impacts
Strategically work on product development including SaaS model
Work with each company to systematically implement solutions and products
Direct report to CEO and company presidents to accelerate data solutions
Personalization is the strategic goal we set, but even going beyond, visions of data innovation in Rakuten is "discovery and maximization of new value." There are lots of valuable products and services that are undervalued in this world; for example, we have seen merchants struggling to do digital marketing but yet can make great products; there are many startup companies that we invest, whose value are not quite yet apparent from sales numbers; people's credit score is also sometimes undervalued just because they don't have the history of borrowing and paying back. Re-assessment of such value is now possible through data. These are the opportunities that are revealed to companies that are willing to look at data, much beyond the currently assigned monetary value of products/services. We believe Rakuten can become the empowerment company that can innovate in this area.
DISD is a collection of highly talented and skilled professionals with strong mind-set of teamwork. The background of people in DISD are quite diverse, from economics, ethnography, physics, computer science, to mathematics from well-known institutions such as MIT and University of Tokyo. Nationality is also diverse, from Belgium, United States, England, China and Japan. We believe such diversity creates better ideas and concepts, that eventually will serve our customers and clients.
In order to maximize our talent, we value the following concepts
1. Have vision. Always strive for excellence and highest excitement.
2. Become a leader. A best leader is also a best follower.
3. Be humble. Respect and support each other. Have strength to rely on others.
4. Be authentic. Talk sincerely but honestly and directly while caring for others.
We are excited to work with the best talent in the world, in order to discover and realize the value with data.
- Translate open-ended requests from management and business partners into clear, concise and measurable analysis questions
- Prioritize analyses and solutions that are tangible, impactful and in line with the team vision
- Retrieve data required for analyses from internal/external sources while ensuring data quality
- Perform statistical analyses, build machine-learning models, or whatever is needed to quantitatively answer business question meaningfully and on time
- Propose solutions and develop prototypes (in collaboration with data engineers if necessary) to demonstrate their potential
- Interpret, present and defend your results to other data scientists, executives or non-tech persons
- Collaborate with business partners, engineers, project managers, researchers and development teams to systemize and maximize solution value
- Be a data (science) evangelist within the company
- Master or greater in Computer Science, Physics, Mathematics, Statistics, Engineering, or relevant field
- At least 2 years of experience doing quantitative analysis
- Good understanding of statistics for data analysis
- Working knowledge of SQL, and at least one scripting language (Python, R, etc.)
- Good written and verbal English skills (TOEIC over 800)
- PhD in Computer Science, Physics, Mathematics, Statistics, Engineering, or relevant field
- Work experience as a data scientist
- At ease with statistics for data analysis (hypothesis testing, Bayesian analysis, time series analysis, experimental design, power and sample sizes, etc.)
- Track record of independently diving into data to find business opportunities, or gain behavioral insights
- Ability to smoothly convey difficult technical concepts to non-specialists
- High achiever with a curious mind and strong attention to detail
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