Head of Data Science & AI

About AXA Hong Kong and Macau

AXA Hong Kong and Macau is a member of the AXA Group, a leading global insurer with presence in 52 markets and serving 92 million customers worldwide. Our purpose is to act for human progress by protecting what matters.

As one of the most diversified insurers in Hong Kong, we offer integrated solutions across Life, Health and General Insurance. We are the largest General Insurance provider and a major Health and Employee Benefits provider. Our aim is to not only be the insurer to provide comprehensive protection to our customers, but also a holistic partner to the individuals, businesses and community we serve. At the core of our service commitment is continuous product & service innovation and customer experience enrichment, which is achieved through actively listening to our customers' needs and leveraging and investing in technology and digital transformation.

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AXA is an equal opportunity employer. We are committed to promoting Inclusion and Diversity (I&D) by creating a work environment where all employees are treated with dignity, respect, and where individual differences are valued. We welcome and treasure diverse profiles to join our big family, and to build an inclusive culture together which allows everyone to maximise their personal potential.

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Reporting directly to the Chief AI Officer (CAIO) of AXA Hong Kong & Macau, the Head of Data Science & AI is responsible for leading the organization's Data Science, Advanced Analytics, and AI development capabilities while supporting the CAIO in driving enterprise-wide Data & AI Transformation.

The successful candidate will lead multidisciplinary teams covering Data Science, Machine Learning, Advanced Analytics, Generative AI, and AI Product Development, ensuring AI solutions deliver measurable business value while complying with AXA's governance, security, risk, and regulatory requirements.

Strategic Leadership & AI Transformation

• Act as a trusted partner to the Chief AI Officer (CAIO) in the execution of AXA Hong Kong & Macau's Data & AI strategy.

Data Science & Advanced Analytics Leadership

• Lead AXA Hong Kong & Macau's Data Science & Analytics function.

AI Solution Development & Model Engineering

• Lead the end-to-end design, development, training, evaluation, deployment, and optimization of AI and Machine Learning solutions.

AI Product Development & Lifecycle Management

• Lead the development and operationalization of enterprise AI products throughout their lifecycle.

MLOps, LLMOps & AI Operations

• Establish and drive enterprise MLOps and LLMOps practices to support production AI solutions.

Business Partnership & Stakeholder Management

• Act as the primary AI and Data Science advisor to business stakeholders.

Responsible AI, Governance & Data Collaboration

• Partner closely with the AI Governance & Data Management team to ensure AI solutions comply with established governance frameworks, policies, and standards.

Collaboration with AI Platform & Innovation Team

• Work closely with the AI Platform & Innovation team to leverage and influence enterprise AI capabilities and platforms.

Qualifications:

• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Information Technology, or related disciplines.
• Minimum 10 years of experience in Data Science, Artificial Intelligence, Machine Learning, Advanced Analytics, or related disciplines, minimum 5 years of leadership experience managing Data Science, Analytics, or AI teams.
• Demonstrated experience developing, training, deploying, and operating AI and Machine Learning solutions in enterprise environments.
• Proven experience delivering business outcomes through AI and advanced analytics.
• Experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and emerging AI technologies.
• Strong experience engaging senior business stakeholders and executive leadership teams.
• Experience in insurance, financial services, banking, consulting, or other highly regulated industries is preferred.