Data Scientist

Job Type
Based on Experience
Japanese Level
English Level
Advanced (TOEIC 860)
Start Date


Great opportunity to work as a data scientist with multi-national and highly skilled team members within one of the top internet service companies.


They are seeking highly motivated data scientists to work together with data engineers to create various data science solutions for the rapidly growing group, which provides 50+ services to millions of users in Japan and around the world.


The department is a newly established department whose mission is to " Create value through data intelligence technology and ecosystem to establish the company as the global innovation company ". They are empowering customers and clients by utilizing the company's rich data. The following are just 2 examples of the department's works.

1. Create excellent User Experience (UX)

2. Empower clients in the platforms the company provides



‐Identify problems and provide solutions which have significant impacts on business

‐Create logics and algorithms to solve problems from both hypothesis drive analysis and data mining analysis with primary focus on business value such as customer experience

‐Implement data-driven scalable solutions with technology that actually functions in the service by collaborating with software engineers

‐Manage the requirement and quality of project and product by working with project/product managers

Required Skills

‐MSc in computer science, statistics, neuroscience, engineering, mathematics, or physics

‐Understanding of foundational statistics concepts and ML algorithms: linear/logistic regression, random forest, boosting, GBM, NNs, etc.

‐Passion for learning (new problem domains, algorithms, tools etc) and for analyzing data

‐Fluency in at least one: Python, Java, Scala, C/C++, Ruby, R

‐Fluency with Unix/Linux systems

‐Ability to access, manage, transfer, integrate and analyze complex datasets, especially using SQL

‐Experience with scikit-learn and pandas (or equivalent tools)

Preferred Skills

‐Ph.D. degree in computer science, statistics, neuroscience, engineering, mathematics, or physics

‐Experience with advanced ML models and concepts: HMMs, CRFs, MRFs, deep learning, regularization etc.

‐Industry experience in data science or related areas

‐Experience with working on large data sets, especially with Hadoop and Spark

‐Experience with distributed databases such as HBase, Redis, CouchBase etc

‐Experience with cloud computing platforms such as AWS

‐Experience with BI, data visualization tools such as Tableau, D3.js

‐Experience with GPU usage