Lead Data Scientist – Underwriting AI

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. This role combines deep technical expertise, people leadership, and strong business partnership to deliver scalable, compliant, and value-generating underwriting capabilities.

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. The role partners closely with underwriting, risk, technology, and regional stakeholders, and supports the Chief AI Officer in delivering the Asia AI Value agenda and building world-class, revenue-generating analytics.

Position Responsibilities:

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

  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 (e.g., medical reports, financial statements, applications)

  Prompt engineering, retrieval-augmented generation (RAG), and evaluation frameworks

  Model orchestration, guardrails, and human-in-the-loop designs

• 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

  AI governance and responsible AI practices

• 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.

When you join our team:

• 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.

About Manulife and John Hancock

Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit .

Manulife is an Equal Opportunity Employer

At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.

It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact <.

Working Arrangement

Hybrid