スキルハウスの採用情報
【大手外資系金融グループ】シニアデータサイエンティスト（Generative AI / Machine Learning）
役職：
【大手外資系金融グループ】シニアデータサイエンティスト（Generative AI / Machine Learning）
雇用形態:
正社員
給与:
12000000.00
勤務時間:
日本語-中上級 (JLPT N2),英語-中上級 (TOEIC 730)
職務内容
Responsibilities:
- Design, develop, and deploy Machine Learning models including classification, regression, clustering, and time-series forecasting.
- Build and implement Generative AI solutions using technologies such as RAG, vector databases, embeddings, AI Agents, prompt engineering, and LLM fine-tuning.
- Develop AI-powered applications including AI Assistants, knowledge search solutions, and intelligent automation platforms.
- Design AI evaluation frameworks and monitor model quality, performance, drift detection, and continuous optimization through MLOps and LLMOps practices.
- Lead AI projects from business requirement gathering through solution design, implementation, testing, production deployment, and operational support.
- Identify business challenges, validate hypotheses through data analysis, and recommend practical AI-driven solutions with measurable business value.
- Collaborate closely with Business, IT, Data Engineering, AI Engineering, and regional/global stakeholders to successfully deliver AI initiatives.
- Drive Responsible AI, AI Governance, model explainability, and regulatory compliance throughout the AI lifecycle.
- Prepare presentations, technical documentation, and business cases for both technical and non-technical stakeholders.
- Mentor junior Data Scientists and establish best practices, technical standards, and development methodologies across the AI team.
Required Skills:
- 5+ years of professional experience in Data Science, Machine Learning, or Artificial Intelligence.
- Recent hands-on experience developing Generative AI applications such as AI Assistants, RAG systems, or Agentic AI solutions.
- Strong expertise in Machine Learning, statistical analysis, feature engineering, model evaluation, and predictive modeling.
- Practical experience with LLM technologies including Azure OpenAI, prompt engineering, embeddings, vector search, and fine-tuning.
- Strong programming skills in Python and SQL.
- Experience with AI frameworks and tools such as LangGraph, AKKA Agentic AI Framework, or similar technologies.
- Experience leading end-to-end AI projects while collaborating with business users, engineering teams, and technical stakeholders.
- Strong communication, presentation, stakeholder management, and mentoring skills.
Why Should You Apply:
- Lead enterprise-scale Generative AI and Machine Learning initiatives with significant business impact.
- Own the complete AI lifecycle—from ideation and model development to governance, production deployment, and continuous improvement.
- Work with modern AI technologies including LLMs, RAG, AI Agents, Azure OpenAI, MLOps, and LLMOps.
- Collaborate with business leaders, engineers, and global AI teams in a diverse international environment.
- Mentor and influence the technical direction of an expanding AI organization while working on high-visibility strategic initiatives.
Company details:
Our client is a leading global financial services organization serving millions of customers across more than 20 countries and territories. The company is recognized as one of the insurance industry's leaders in Artificial Intelligence adoption, consistently investing in Generative AI, Machine Learning, and enterprise digital transformation initiatives. Its AI organization works closely with regional and global teams to develop innovative, production-ready AI solutions that enhance customer experience, improve business operations, and accelerate innovation across the enterprise.
The company offers a collaborative international environment, strong investment in employee development, flexible working arrangements, and long-term career growth opportunities while fostering a culture of innovation, responsible AI, and continuous learning.
Working Hours: Monday–Friday, 9:00–17:00
Working Style: Hybrid (2 days remote work per week)
Work Location: Tokyo
Holidays: Weekends, national holidays, year-end holidays, paid leave, and additional special leave.
Benefits: Comprehensive social insurance, retirement plan, professional training programs, language learning support, childcare and family care programs, wellness benefits, and other employee support initiatives.
