Rakuten

Data Scientist - AI & Data Consulting Department (AIDC)

Tokyo, Japan
AWS GCP SQL Machine Learning Python Pandas Spark
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 Data Science Consulting Department (DSCD) 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 

- Japanese proficiency

#technologyservicediv

#datascientist

Languages:

English (Overall - 3 - Advanced)

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