[E-only] Lead Data Scientist | #1 Ranked Reinsurer in Japan

An exceptional opportunity for a senior data scientist to apply advanced analytics and statistical modeling directly to high-value underwriting, risk, and financial decisions in one of the world’s most sophisticated insurance markets. Japanese proficiency is not mandatory, but a very strong advantage!

Why You Should Apply:

- Direct Business Impact – Your models will influence underwriting, pricing, longevity risk, and capital decisions tied to large-scale reinsurance transactions.
- Global × Japan Exposure – Operate at the intersection of global analytics and Japan’s highly advanced insurance market, collaborating with international stakeholders in an English-speaking environment.
- Senior-Level Influence – Act as a trusted individual contributor, shaping modeling approaches and analytical direction — not just executing predefined tasks.
- Cross-Functional Leadership – Work closely with actuarial, underwriting, finance, and product teams where analytics is central to strategic decision-making.
Long-Term, Meaningful Challenges – Apply advanced data science to complex, real-world risk problems within a stable, globally respected organization.

 

Responsibilities:

- Design and validate predictive and machine learning models for underwriting, risk, and portfolio analysis
- Analyze large, complex datasets to generate insights that support business and risk decisions
- Develop and apply AI and Generative AI solutions, including LLM-based and agent-driven workflows
- Translate business problems into practical, scalable data science solutions
- Collaborate with cross-functional and client-facing stakeholders across the organization
- Communicate analytical results clearly to both technical and non-technical audiences
- Stay current with emerging data sources and AI technologies
- Provide technical guidance to junior data scientists as needed (no formal people management)

Required Skills:

- 10+ years of experience in data science, analytics, or statistical modeling
- Strong hands-on experience with Python and/or R
- Solid background in statistical and machine learning methods (e.g., GLM, ML, deep learning, time series)
- Practical experience with Generative AI and LLM-based solutions
- Experience deploying models and working with MLOps and governance frameworks
- Industry experience in insurance, reinsurance, finance, or risk-related domains preferred
- Strong communication skills and ability to work independently across teams