【Full Remote】Bilingual Data Scientist【大手プライム上場】

One of our top clients, a well-established technology company listed on the Tokyo Stock Exchange, is currently looking for a Senior Data Scientist to join its growing data organization.

Built on a strong foundation of consumer-facing digital services, the company has successfully expanded into high-impact areas such as Healthcare and Education DX, using technology and data to address real societal challenges.

With a stable business foundation and continued growth, the company is investing further in advanced Data Science, Machine Learning, Generative AI, and data-driven decision-making capabilities across the organization.

This is a senior-level position where you will lead analytical and Machine Learning initiatives from problem definition through implementation and business recommendations.

You will work closely with Product, Engineering, and Business teams, delivering actionable insights, developing scalable analytical solutions, and helping establish best practices across analytics, Machine Learning, and data management.

Why Apply?

About the Role

We are looking for an experienced Senior Data Scientist who can independently lead Data Science and Analytics projects while collaborating closely with both technical and business stakeholders.

The role combines advanced analytics, Machine Learning, data infrastructure collaboration, and the practical application of Large Language Models (LLMs).

You will also have the opportunity to contribute to technical standards and mentor other Data Scientists within the organization.

Responsibilities

Analytics & Decision Support

• Lead analytical projects supporting business and product decision-making

• Design metrics and analytical frameworks to evaluate initiatives, product performance, and business outcomes

• Conduct segmentation, trend analysis, experimentation, and other advanced analytical studies

• Translate complex or ambiguous business questions into structured analytical approaches

• Create dashboards, reports, and presentations for stakeholders

• Clearly communicate analytical findings, recommendations, assumptions, and limitations to both technical and non-technical stakeholders

Machine Learning & LLM

• Develop and deploy predictive and segmentation Machine Learning models

• Build and maintain model monitoring processes covering performance, drift, and data quality

• Apply Large Language Models to real-world business workflows through prompt design, orchestration, and evaluation

• Contribute to LLM adaptation approaches including RAG and fine-tuning

• Define methodologies for evaluating model quality, robustness, and business impact

• Promote Machine Learning best practices and provide technical guidance to other team members

Data Integration & Analytics Infrastructure

• Design and maintain analytical datasets integrating multiple data sources

• Establish and document consistent metric definitions and reporting standards

• Collaborate with Data Engineers to improve data structures, tracking, and data quality

• Promote reproducible analytics, documentation, and data governance practices

• Contribute to the development of scalable analytics capabilities and infrastructure across multiple teams

Requirements

Requirements

Must-have Skills

• 5+ years of professional experience in Data Science, Analytics, Machine Learning, or a closely related field

• Advanced SQL skills and hands-on experience with cloud data warehouses such as BigQuery, Snowflake, or Amazon Redshift

• Strong Python or R skills for data analysis and Machine Learning

• Strong understanding of statistics, experimentation, and analytical methodologies

• Hands-on experience developing and deploying Machine Learning models

• Ability to independently lead analytical projects from problem definition through analysis, implementation, and business recommendations

• Experience collaborating with both technical teams and business stakeholders

• Strong written and verbal communication skills

Preferred Skills

• Experience mentoring junior Data Scientists or leading analytical workstreams

• Experience with BI and visualization tools such as Looker, Tableau, or Power BI

• Experience with data integration, metric standardization, documentation, and data governance

• Experience with MLOps, model monitoring, and Machine Learning lifecycle management

• Hands-on experience developing, evaluating, or deploying LLM applications

• Experience with Generative AI technologies such as RAG, prompt engineering, LLM evaluation, or fine-tuning

Language Requirements

Benefits