■Recruitment Background
“Changing clothes, changing common sense, changing the world.” This is the Fast Retailing Group’s statement. Through “clothing”—an indispensable part of people’s lives around the world—we aim to become the most needed and beloved brand in the world. Under the LifeWear concept, we utilize an integrated process spanning 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 desire at the highest level and becoming a company that improves society alongside our own growth. 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 global business growth, it is essential to automate and advance our 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 form the core of these efforts.

■ Department Overview
The Digital Business Transformation Services Department, to which you will be assigned, is on a mission to envision the "ideal state" of operations from the customer’s perspective and lead business transformation using the latest digital technologies. We are accelerating the in-house development of e-commerce and store systems, core supply chain 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 business divisions.
The Data Analysis Team, to which you will be assigned, consists of members with high levels of expertise in data science. Working closely with teams in IT domains such as e-commerce and SCM, they tackle challenges and lead 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—such as various cloud services—and cutting-edge technologies.

■Job Description
You will be responsible for the following tasks in collaboration with business units and engineers:
・Defining data challenges: You will collaborate with business units to gain a deep understanding of business processes and define challenges to be solved through data science.
・Analysis & Model Design/Development: Select the appropriate approach—such as statistical analysis, machine learning, or mathematical optimization—to design, implement, and validate high-precision, business-relevant models. Additionally, collect and preprocess data as needed.
・Implementation of Results: Leveraging your data science expertise, you will present proposals for operational improvements to stakeholders based on the results obtained, guiding the process through implementation to the creation 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 for a demand forecasting model deployed globally
・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 multi-agent systems using solutions from major LLM providers, as well as implementing AI that understands business context by leveraging the low-code foundation of the Power Platform
・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

*The Job Description may change within the scope of duties related to various headquarters departments due to department transfers or organizational changes.

■ Career Path
Upon joining the company, you will start on 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 across various business areas and project themes within the team, acquiring broad domain knowledge.
・For those interested in team management, 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 solved through data science
・In addition to a college-level understanding of basic mathematics (statistics, linear algebra, etc.), the ability to perform any of the following 1–3, or possess equivalent specialized knowledge in computer science
1. (Statistics) Possesses statistical knowledge equivalent to passing Level 2 of the Statistical Examination and is capable of building statistical models and conducting analyses
2. (Machine Learning) Understanding of common machine learning algorithms, with the ability to select and apply appropriate methods
3. (Mathematical Optimization) Understands linear and nonlinear programming problems and can perform modeling independently
・Ability to implement analytical models and perform data collection, processing, and preprocessing using Python, SQL, etc.
・Experience proposing and implementing business process improvements based on results obtained by leveraging the above specialized knowledge and engineering skills. Experience implementing models into business systems and embedding them into actual business processes.

■ Desired Experience, Skills, and Abilities
・Master’s or doctoral degrees in data science-related fields, or professional certifications such as the Level 1 Statistics Certification
・Experience in data analysis and operational 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 leveraging data science expertise to generate significant business results
・Communication skills to clearly explain the results, limitations, and risks of data science to business stakeholders and executive management
・Proven track record of participation in the technical community, including publishing papers, presenting at academic conferences, participating in competitive programming and data analysis competitions such as Kaggle, and contributing to open-source projects
・Proven track record in team building through code reviews, knowledge sharing, and technical mentoring of junior members
・Experience collaborating with international team members or studying abroad

■Company Name
Fast Retailing Co., Ltd.

■Employment Type
Full-time Employee (Permanent position, 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 positions
・Flexible work hours
Standard daily working hours: 8 hours; Break: 1 hour
Core hours: 9:00 AM–2:00 PM
Flexible hours…6:00 AM–9:00 AM and 2:00 PM–8:00 PM (Overtime work may occur)

・Supervisors
Based on the working hours of the employee’s department, with the decision left to the employee

■ Holidays and Leave
Two days off per week (Saturdays and Sundays; national holidays are working days) Annual paid leave, special leave (including bereavement leave), childcare and nursing care leave systems, etc.
*In addition to paid leave, 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 the employee belongs)

■Insurance Coverage
Social Insurance (Health Insurance, Employees' Pension Insurance, Employment Insurance, Workers' Accident Compensation Insurance, Long-Term Care Insurance)

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

■Other
・We actively recruit mid-career professionals across our 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 suggest opportunities at other companies or positions 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.