Lead Data Scientist – Underwriting

The Lead Data Scientist – Underwriting is a senior leadership role responsible for driving regional and BU-level AI, ML, and Generative AI solutions to transform underwriting decision-making across Asia.

You will lead and grow a team of data scientists focused on underwriting AI, while also acting as a hands-on technical leader shaping advanced predictive, prescriptive, and generative solutions.

Technical & Business Leadership

• Lead the design, development, and deployment of AI, ML, and Generative AI solutions supporting underwriting use cases, including underwriting summarization and document intelligence, risk assessment and decision support, straight-through processing (STP) and workflow automation, and data-driven underwriting rules optimization.
• Translate complex underwriting and business problems into scalable analytical and GenAI solutions with measurable business outcomes.
• Drive adoption of AI solutions by embedding them into end-to-end underwriting workflows, ensuring usability, governance, and regulatory compliance.
• Partner with reinsurers, vendors, and external technology providers to co-develop or integrate advanced underwriting solutions.
• Lead, coach, and develop a high-performing team of data scientists focused on underwriting AI and analytics.

Generative AI & Advanced Analytics

• Lead the application of AI and especially GenAI in underwriting, including Large Language Models (LLMs) for text-heavy underwriting data, prompt engineering, retrieval-augmented generation (RAG), and evaluation frameworks.
• Ensure AI solutions are responsible, explainable, auditable, and compliant with internal AI governance and regulatory expectations.
• Establish standards for model lifecycle management, performance monitoring, and value tracking for AI and GenAI solutions.

Strategy, Governance & Stakeholder Management

• Contribute to AI and data strategy, focusing on data optimization, monetization, and external data enrichment.
• Collaborate with global and regional teams to define common modeling standards, governance, and reusable AI assets, aligned with AI CoE guidelines.
• Maintain a regional/global model repository to track models in use, performance, and risks.
• Act as a trusted advisor to underwriting and business leaders, influencing prioritization and investment decisions.
• Proactively identify risks, data challenges, and stakeholder conflicts, and drive alignment and mitigation plans.

Required Qualifications:

• 10+ years of experience in AI, machine learning, or advanced analytics, preferably within financial services.
• Strong underwriting, insurance, or reinsurance domain knowledge (highly preferred).
• Proven experience leading complex analytics initiatives in highly regulated environments.

Technical & GenAI Skills

• Strong hands-on expertise in ML/statistical modeling, segmentation, and underwriting or claims analytics.
• Advanced proficiency in Python, SQL, and common data science toolchains (R, SAS a plus).
• Practical experience with Generative AI, including Large Language Models (LLMs), prompt engineering and RAG architectures, model evaluation, bias mitigation, and explainability.
• Experience with cloud and big data platforms (e.g., Azure, Spark, Databricks, Hadoop).
• Strong understanding of deploying models into production, including monitoring and lifecycle management.

Leadership & Communication

• Demonstrated ability to lead and scale teams, mentor data scientists, and manage ambiguity.
• Strong stakeholder management skills with the ability to influence senior leaders across regions.
• Excellent communication and presentation skills, translating technical concepts into business language.

Benefits:

• We’ll empower you to learn and grow the career you want.
• We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
• As part of our global team, we’ll support you in shaping the future you want to see.