Recruitment Background

“Changing clothes, changing common sense, changing the world.” This is the Fast Retailing Group’s mission statement. Through “clothing”—an indispensable part of people’s lives around the world—we aim to become the world’s most needed and beloved brand. Guided by the LifeWear concept, we utilize an integrated process—from material sourcing to planning, production, and sales—to offer unique products made with high-quality and functional materials at prices accessible to everyone.Our revenue has reached 3 trillion yen in the 40 years since our founding, and we have set a long-term goal of 10 trillion yen in revenue. This does not mean that revenue growth is an end in itself; rather, it signifies our commitment to delivering the services our customers seek at the highest level and becoming a company that improves society as we grow. We view the current period of transformation as our “Fourth Founding,” and one of the drivers of this transformation is the utilization of technology.
To carry out such disruptive transformations and achieve dramatic business growth on a global scale, it is essential to automate and enhance business operations through the implementation of intelligent systems that integrate vast amounts of data with the power of science. For this position, we are seeking a Data Scientist to lead the utilization of data analysis and data science, which are central to these efforts.

Department Overview

The Digital Business Transformation Services Department, to which you will be assigned, has a mission to envision the “ideal state” of business operations from the customer’s perspective and to lead business transformation using the latest digital technologies. The department is accelerating the in-house development of e-commerce and store systems, supply chain core systems, and the AI algorithms integrated into them. A diverse team of specialists—including project managers, business analysts, in-house development engineers, data scientists, and UI/UX designers—collaborates closely with the business divisions.
The Data Analysis Team, to which you will be assigned, consists of members with high levels of expertise in data science. They work closely with teams in the IT department’s operational areas—such as e-commerce and SCM—to tackle challenges and are responsible for initiatives to revolutionize business processes across the entire Fast Retailing Group through data science.
We drive analysis and development efforts on the company-wide centralized data platform, actively leveraging modern development environments—including various cloud services—and cutting-edge technologies.

Job Description

You will be responsible for the following series of tasks while collaborating with business units and engineers.

• Defining Data Challenges: You will work closely with business units to gain a deep understanding of business processes and define challenges to be solved through data science.
• Analysis & Model Design and Development: You will select the appropriate approach—such as statistical analysis, machine learning, or mathematical optimization—to design, implement, and validate highly accurate and business-relevant models. You will also collect and preprocess data as needed.
• Implementation of Results: Leveraging your data science expertise, you will present proposals for operational improvements to relevant stakeholders based on the results obtained, and guide the process through implementation to the delivery of tangible outcomes. You will also integrate models into business systems to embed data science outcomes into operational processes.

Examples of projects include the following:

• Multiple forecasting projects within a globally deployed demand forecasting model
• Design and development of AI systems to categorize and analyze feedback from customers and store staff, as well as AI systems for extracting supply chain KPIs, anomaly detection, and decision support
• Building a multi-agent system using solutions from a major LLM provider, as well as implementing AI that understands business context by leveraging the Power Platform’s low-code framework
• Design, development, and optimization of production planning algorithms utilizing demand forecasting data
• Analysis and accuracy improvement of demand forecasting models by individual store and product
• Building a simulation platform covering the entire supply chain and conducting “what-if” analyses using it
• Improving e-commerce search accuracy using AI, and supporting the planning and execution of digital marketing campaigns

*The Job Description is subject to change within the scope of duties related to each department at headquarters due to department transfers or organizational changes.

Career Path

Upon joining the company, you will begin with a project where you can best utilize your skills, taking into account your preferences and experience. The following career paths are available in the future:

• As a data scientist, you will deepen your expertise while gaining experience on projects across various business areas and themes within your team, thereby acquiring broad domain knowledge.
• For those interested in taking on team management roles, you will gradually expand your leadership responsibilities and may eventually lead the organization as a team manager.
• There are also opportunities for transfers within the IT department or to business divisions with which we collaborate (such as Product Planning, Production, Logistics, and Marketing).

Required Experience, Skills, and Abilities

• At least 3 years of practical experience as a data scientist
• Experience collaborating with business teams to gain a deep understanding of business processes and independently defining challenges to be addressed through data science
• In addition to an understanding of basic mathematics at the undergraduate liberal arts level (such as statistics and linear algebra), the candidate must be capable of performing any one of the following tasks 1–3, or possess other specialized knowledge in information science equivalent to these:

1. (Statistics) Possesses statistical knowledge equivalent to passing Level 2 of the Statistical Certification Exam and is capable of building statistical models and conducting analyses
2. (Machine Learning) Understanding of algorithms for common machine learning methods, and the ability to select and apply appropriate techniques
3. (Mathematical Optimization) Understands linear and nonlinear programming problems and can model them independently

• Ability to implement analytical models and collect, process, and preprocess data using Python, SQL, and other tools
• Experience proposing and implementing business process improvements based on results obtained by applying the specialized knowledge and engineering skills listed above. Experience implementing models into business systems and integrating them into actual business processes.

Desired Experience, Skills, and Abilities

• Master’s or doctoral degree in a data science-related field, or professional certifications such as the Level 1 Statistics Certification
• Experience in data analysis and business knowledge in the retail, apparel, or supply chain sectors
• Experience implementing and utilizing generative AI and agent technologies in actual business systems
• A proven track record of generating significant business results by leveraging data science expertise
• Communication skills to clearly explain the results, limitations, and risks of data science to business unit stakeholders and executive management
• A track record of involvement in the technical community, including published papers, conference presentations, participation in competitive programming and data analysis competitions (such as Kaggle), and contributions to open-source software (OSS) projects
• A proven track record of team building through code reviews, knowledge sharing, and providing technical guidance to junior team members
• Experience collaborating with international team members or studying abroad

Company Name

Fast Retailing Co., Ltd.

Employment Type

Full-time Employee (Permanent, with a 3-month probationary period)

Annual Salary

• Annual Salary Range: 7.04 million yen–20 million yen (Monthly Salary: 410,000 yen–1.1 million yen)
• Allowances: Commuting allowance, overtime pay, etc. (*All subject to company regulations)
• Bonuses: Semi-annual bonuses twice a year, year-end bonus (eligibility and amount determined based on company performance and performance evaluations)
• Promotions twice a year (determined based on performance evaluations)

*Salary will be determined based on company regulations, taking into account your previous annual income and experience, and is not limited to the figures listed above.

Working Hours

Flexible work hours or managerial/supervisory position

• Flexible work schedule

Standard daily working hours: 8 hours; Break: 1 hour
Core hours: 9:00 a.m. to 2:00 p.m.
Flexible hours…6:00 a.m.–9:00 a.m. and 2:00 p.m.–8:00 p.m. Overtime may be required

• Supervisors

Based on the working hours of the employee’s department; left to the employee’s discretion

Holidays and Leave

Two days off per week (Saturdays and Sundays; national holidays are considered workdays). Annual paid leave, special leave and bereavement leave, childcare and family care leave systems, etc.
*In addition to paid vacation, special leave is granted in the first and second halves of the fiscal year (the number of days granted varies depending on employment status and the company to which you belong)

Insurance Coverage

Social Insurance (Health Insurance, Employees’ Pension Insurance, Unemployment Insurance, Workers’ Compensation Insurance, Long-Term Care Insurance)

Employee Benefits

Employee stock ownership plan, mutual aid association, partner benefit programs, employee discount program, cafeteria, dedicated shuttle bus (for commuting to the Ariake office), defined contribution pension plan

Other

• Our company actively recruits mid-career professionals across various Group companies (Fast Retailing, UNIQLO, GU, etc.). We would appreciate it if you could review the information below and consider applying.
• You may apply to multiple companies within the Fast Retailing Group simultaneously. However, please note that even if the selection process proceeds at multiple companies, you can only advance to the final selection stage for one position at a time.
• Based on your submitted resume and interview performance, we may contact you to discuss other positions at different companies within the Fast Retailing Group.
• Measures Against Secondhand Smoke: Smoking is prohibited on the premises and indoors; we do not have designated smoking rooms. (Smoking is prohibited during working hours, including break times.)

Ariake Headquarters: 1-6-7 Ariake, Koto-ku, Tokyo, UNIQLO CITY
*Your location may be changed to a location designated by the company, including overseas locations.