发布于 2026-07-03
英文原文
业务分析师 - FMCG客户战略部,乐天24
消費財&総合家電ダイレクト事業 FMCG顧客戦略部:マーケティンググループ データアナリスト(楽天24)(C&M)
楽天グループ
| 职种 | 数据与人工智能 | 雇用形态 | — |
|---|---|---|---|
| 工作地点 | 日本 | 薪资 | 面议 |
职位概要
乐天集团旗下乐天24是2010年成立的D2C电商平台,主要销售日用品、食品、饮料、化妆品、母婴、宠物及健康用品,依托乐天积分生态和集团客户基础,已成为乐天集团增长的核心业务之一。FMCG客户战略部负责利用乐天24及乐天市场的用户行为与市场数据,提升用户获取与激活、提高ARPU。现招聘业务分析师,主要职责包括:设计客户战略部门及项目级KPI,并从多维度审视KPI及波动应对;搭建和运营KPI监控环境;开发与维护GMS、转化率、ARPU等KPI的预测模型;通过数据分析支持营销决策并向内部利益相关方汇报。要求具备扎实的数据分析能力,积极主动,能适应快速变化的业务环境。该岗位可全面参与从KPI设计、监控环境构建到预测模型运营的数据利用全流程,未来可向数据战略规划与管理方向发展。
职位描述
Job Description: Business Overview The Rakuten Group offers over 70 services in a wide range of fields both in Japan and overseas, including internet services such as e-commerce, travel and digital content; fintech (financial) services such as credit cards, banking, securities, electronic money and smartphone app payments; mobile services such as mobile carrier business; and professional sports. By organically linking these services together through membership centered on Rakuten members, we have formed a unique "Rakuten Ecosystem (economic sphere)." *Rakuten's business in numbersã https://corp.rakuten.co.jp/careers/services/ Department OverviewRakuten 24 was established in 2010 to meet the rapidly expanding online purchasing needs for daily necessities, household goods, and consumables, particularly the demand for affordable and speedy delivery of bulky daily essentials and heavy beverages. This was a strategic challenge, aiming to leverage Rakuten Group's robust platform and logistics network to become an infrastructure supporting consumers' "daily lives." Currently, Rakuten 24 operates as a direct-to-consumer (D2C) e-commerce site primarily offering daily necessities, food, beverages, cosmetics, baby products, pet supplies, and healthcare items, steadily increasing its market share within the e-commerce goods sector. Thanks to the convenience of one-stop shopping for daily essentials, its integration with the Rakuten Points ecosystem, and the strong customer base of the Rakuten Group, Rakuten 24 is favored by many customers as a "daily use" platform among numerous e-commerce sites. Consequently, it contributes to the overall expansion of Gross Merchandise Sales (GMS) on Rakuten Ichiba and has become one of the key businesses driving the growth of the entire Rakuten Group. As a rare D2C e-commerce business within Rakuten, Rakuten 24 allows direct involvement in end-user marketing, as well as a wide range of decision-making processes, including product assortment and supply chain management. Among its departments, the Customer Strategy Section (or Department) is tasked with solving marketing challenges by leveraging data from Rakuten 24 and Rakuten Ichiba. Its primary mission is to increase the number of Rakuten 24 users (both new acquisitions and reactivation of lapsed users) and promote initiatives to improve Average Revenue Per User (ARPU). Given the immense scale of Rakuten 24, utilized by a vast number of users, and the fast-paced nature of the industry, there are abundant growth opportunities. Position: Why We Hire Rakuten 24 is rapidly expanding its market share in the daily essentials e-commerce sector, becoming a pivotal engine for the overall growth of the Rakuten Group. To further accelerate this momentum and remain an "indispensable" partner for our customers, we must dramatically enhance the precision and speed of our data-driven decision-making. Our FMCG Customer Strategy Department is dedicated to leveraging extensive user behavior and market data to deeply understand individual customer needs and deliver optimal experiences. Currently, our organization faces challenges in fully utilizing the vast amount of data we accumulate daily, or in doing so efficiently. There is a pressing need for greater expertise and drive, particularly in areas such as precise KPI design to maximize marketing effectiveness and drive customer behavioral change, ongoing performance monitoring, and future forecasting. This is why we are now looking for new team members who possess strong data analysis expertise and are eager to shape the future of our business with us. At Rakuten 24, the immense volume of data and unparalleled growth opportunities offer a unique chance to fully apply your analytical skills and find significant satisfaction in impacting the core of our operations. Join us in pioneering Rakuten 24's future through data-driven insights, as we strive to be the ultimate life partner enriching our customers' everyday lives. attraction - At Rakuten 24, a growing business undergoing a data-driven transformation, your analysis will drive the next growth strategy and create a significant impact that moves the core of the business. - Our team is highly motivated to embrace new initiatives without being bound by past practices. This environment ensures your proactive actions are reflected in numerous decision-making processes. - You will experience the entire data utilization process, from KPI design to monitoring environment construction and predictive model operation, allowing you to hone your comprehensive skills as a "Business Analyst" who leads business problem-solving. In the future, a wide range of career paths will open up, including data strategy planning and management. - Rakuten 24 belongs to "Rakuten Ichiba," one of Japan's largest e-commerce platforms, and the robust ecosystem of the Rakuten Group. The overwhelming scale of data, unavailable at other companies, and the unique perspective that allows you to overview customers' entire lifestyles, create a one-of-a-kind environment where your analytical skills can be maximized. Position Details Job Summary: The primary responsibilities for this role involve conducting analyses to support marketing decision-making within the FMCG Customer Strategy Department and presenting these insights to internal stakeholders. Key tasks include: designing Key Performance Indicators (KPIs); building and operating KPI monitoring environments; and developing and maintaining predictive models for KPIs such as Gross Merchandise Sales (GMS), conversion rates, Average Revenue Per User (ARPU), etc. Key Responsibilities 1. KPI Design Design KPIs to be tracked by the Customer Strategy Department, as well as specific KPIs for individual projects.Thoroughly consider how these KPIs should be viewed (e.g., from various perspectives/segmentations) and what actions should be taken based on their fluctuations.ãContinuously review and revise KPIs as needed, in response to evolving business conditions. 2. KPI Monitoring Environment Development and Operation Build and operate an environment that allows anyone to easily and efficiently monitor the designed KPIs.This includes end-to-end responsibility from evaluating necessary tools, designing data marts, to designing and implementing output visualizations. 3. KPI Predictive Model Development and Operation Develop models to predict KPIs using statistical modeling and machine learning techniques.ãEfficiently evaluate and update these models on an ongoing basis. Furthermore, it is essential to explain the prediction results, requiring the establishment of methods that balance KPI prediction accuracy with interpretability. Work Environment Our Organization is - Consumables & Electronics Direct Business (CEDB): Approx. 250 employees - FMCG Customer Strategy Section, Marketing Group: 11 personnel Vice Manager: 1 Assistant Managers: 2 Team Members: 8 Composition (New Graduate vs. Mid-Career): 50% : 50% Mid-Career Hires Background - Data Analyst experience at consulting firms - Data Scientist experience at online media and e-commerce companies Career Path Examples - Promoted to Team Leader after 3 years, currently active as a Manager candidate. - Promoted to Team Leader after 10 months, currently active as a Manager candidate. - Active as the Forecast Lead for multiple services after 2 years. Mandatory Qualifications: - Practical experience using SQL (preferably 4 years or more) - Skills in processing and aggregating large-scale data (hundreds of billions of records or more) - Ability to design data marts for efficient data processing - Experience in building and operating predictive models using programming languages such as Python/R, combined with machine learning and statistical methods (3+ years preferred - Ability to clearly explain analytical findings to others - Strong structural thinking skills to organize abstract concepts Desired Qualifications: - Experience in designing