Machine Learning Engineer

Contract type
Web Marketing / Advertising
Company Type
日系企業/Japanese Company
5 Million yen〜12 Million yen
Japanese Level
ビジネスレベル/Business Level
English Level
Other Language Skills

Job Description

The group's data is accumulated enormously every day from services that have the top share in Japan. The company's cloud engineers handle this data and contribute to the creation of new value in a wide range of areas. The Data Promotion Office is an organization responsible for data utilization, data governance management, data product development and operation in the company. Currently, there are about 300 employees, and employees with various expertise in data science/engineering/business belong to it. ■ Style aimed at by the Data Promotion Office They aim for a style in which engineers and data scientists work across all business areas to achieve business expansion and personal growth at the same time. ■ The future image of the Data Promotion Office ・To proceed with maintenance so that 45,000 employees can use data safely and freely. ・ Rather than only some engineers and data scientists using data, using data with all employees causes “unpredictable big changes” ・ To create an environment where data can be utilized and to create a future that one cannot imagine, data can be safely and freely used, and the ground is steadily solidified for the next generation of excellent people. ・ To "science and engineering" the core competencies that generate profits. Establish a style of growth with the power of technology and strengthen business competitiveness [Role of work] ・ Planning and promotion of short-term and medium-term machine learning utilization measures ・ Responsible for developing applications using machine learning ・ Model design and implementation ・ Enhance and operate the system in charge [Specific business example] ・ Project planning/promotion / review, process improvement ・ Achievement of KPI / QCD for project formulation and system development ・ Achievement of SLA system goals in the system in charge ・ Formulation of a refactoring plan to improve the value of the system in charge ・ Development and operation of the recommendation system ・ UX improvement using data science such as search optimization ・ Connection to services of algorithms based on machine learning, natural language processing, image analysis, etc. An example of the development environment 【Development environment】 ・ Programming language Python, SQL, Hive / Spark, etc. ·infrastructure GCP (BigQuery, etc.) AWS (EC2, EMR, Redis, S3, etc.) ・ Team development tools JIRA, Confluence, GHE, Bitbucket, Gitlab / Gitlab CI, Slack, etc.

Required skills

(REQUIREMENTS) For business issues, you can appropriately select statistical analysis/machine learning methods, model them yourself, and output them. Understand the principles of descriptive statistics, inference statistics, and basic machine learning algorithms. Based on the conceptual design, as a member, you can program at the production level as you intended. (WELCOME) Can create requirements definition and necessary documents for a single project. You can organize the requirements for integrating multiple data sources and design your system. Understand the contents of papers and conference presentations related to data science, and be able to implement and evaluate prototypes by yourself. Appropriate programming can be performed while being aware of various restrictions such as computational complexity, memory utilization efficiency, data type, library usage, and platform to be implemented. Understands the basics of algorithms and programming languages ​​and is not restricted by the implementation language.