Senior Data Scientist, Network Intelligence & Analytics Section Applied Analytics & AI Department (RMI AI & Data Supervisory Dep)

Rakuten

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profile Job Location:

Tokyo - Japan

profile Monthly Salary: Not Disclosed
Posted on: 30+ days ago
Vacancies: 1 Vacancy

Job Summary

Job Description:

About Organization

This role sits at the intersection of AI innovation and business strategy. The Data Scientist will play a central role in developing and deploying AI/ML models uncovering behavioral insights from large-scale customer and network data and translating those insights into strategic business outcomes. This position demands both technical depth and strategic thinking ideal for someone who thrives in fast-moving data-rich environments and can work independently while collaborating across technical and business teams. This role offers the opportunity to analyze some of Japans most diverse customer datasets drive AI-driven insights and shape how data is used to make smarter faster decisions across multiple business domains.

Job Duties

The Data Scientist will be responsible for:

Model Development & Deployment:Building validating and deploying machine learning and AI models for customer segmentation churn prediction and behavioral analysis.

Data Handling & Analysis:Working with large volumes of structured and unstructured data (e.g. customer usage transactions geolocation and network patterns). Identifying patterns anomalies and commercial opportunities through advanced statistical and predictive analytics.

Insight Translation & Strategy:Translating analytical outcomes into clear business recommendations that improve acquisition retention and monetization strategies. Developing frameworks and dashboards to measure market impact customer engagement and shop-level performance.

Collaboration & Improvement:Collaborating with data engineering product and marketing teams to operationalize models and insights. Contributing to the continuous improvement of data quality processes and automation.

Mentorship:Supporting and mentoring junior analysts as the team expands ensuring analytical consistency and rigor.

Minimum Qualifications

  • Experience:10 years in data science advanced analytics or applied machine/deep learning and AI.

  • Technical Skills:Strong proficiency in Python SQL and ML libraries (Scikit-learn TensorFlow PyTorch).

  • Analytical Expertise:Strong grasp of statistical modeling causal inference forecasting and segmentation techniques.

  • Data Handling:Proven experience working with large complex datasets (customer behavior network or related).

  • Communication:Ability to convert data-driven findings into concise narratives and strategic insights for non-technical audiences.

  • Domain Awareness:Understanding of telecom or digital platform ecosystems particularly the Japanese market. Japanese work culture or willingness to learn is essential.

  • Mindset:Independent detail-oriented and outcome-driven. Comfortable with ambiguity and capable of navigating it effectively.

Preferred Qualifications

  • Demonstrated experience linking analytics to tangible business impact (e.g. improved conversion reduced churn).

  • Ability to design end-to-end pipelines from hypothesis and feature design to deployment and validation.

  • Curiosity to explore new AI/ML techniques and applications that can enhance customer experience or revenue potential.

  • Strong organizational and presentation skills with a structured approach to problem-solving.

  • Experience with big data technologies such as Spark Hadoop or cloud environments like GCP/AWS.


Required Experience:

Manager

Job Description:About OrganizationThis role sits at the intersection of AI innovation and business strategy. The Data Scientist will play a central role in developing and deploying AI/ML models uncovering behavioral insights from large-scale customer and network data and translating those insights i...
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Key Skills

  • Adobe Analytics
  • Data Analytics
  • SQL
  • Attribution Modeling
  • Power BI
  • R
  • Regression Analysis
  • Data Visualization
  • Tableau
  • Data Mining
  • SAS
  • Analytics

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