Data Analyst(Rakuten24) - FMCG Customer Strategy Department, Consumables & Electronics Direct Business

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 numbers　
https://corp.rakuten.co.jp/careers/services/

Department Overview

Rakuten24 is one of the few direct-to-consumer e-commerce platforms operated by Rakuten, specializing in a wide range of products including daily necessities, food, beverages, cosmetics, baby products, pet supplies, and healthcare items. Through this platform, we aim to drive the growth of Rakuten Ichiba and the broader Rakuten Group.
This unique platform offers opportunities to engage in comprehensive decision-making processes, including direct marketing to end-users, product assortment, and supply chain management.
The Marketing & Planning Division is dedicated to addressing challenges through data-driven strategies for both Rakuten24 and Rakuten Ichiba. Our primary mission is to increase the user base of Rakuten24, including attracting new users and re-engaging former users, as well as implementing strategies to enhance ARPU (Average Revenue Per User).
Rakuten 24, which is used by a vast number of users, offers a significant scale, and there are many growth opportunities precisely because it's an industry with a rapid pace of change.

Position:

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.　Continuously 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.　Efficiently 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:

The team consists of 8 men and 2 women. Roughly half of the team members are mid-career hires, while the other half are recent graduates. This is a highly motivated team eager to undertake new initiatives without being constrained by past practices. Your proactive actions will significantly influence many of our decisions.

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 and implementing analytics infrastructure
・Experience in data visualization using BI tools (e.g., Looker Studio, Tableau)
・Experience in building BI tools
・Experience working at a consulting firm (preferably 3 years or more)
・Graduate-level research experience in machine learning and statistics
・Project management experience
・Knowledge or experience in manufacturing business and e-commerce (EC)

Others:

Work Location:
Rakuten Crimson House, Futako-Tamagawa

#business #CRM #marketing #analist #EC #eCommerce #commerce #RakutenIchiba #Rakuten24 

Languages:

English (Overall - 3 - Advanced), Japanese (Overall - 4 - Fluent)