Associate Director, Data Science

Malaysia·Kuala Lumpurexecutive

Data ScienceData & AI

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Quick Summary

Key Responsibilities

Build, lead, coach and retain a diverse team of data scientists and AI engineers, creating clear standards, career pathways and a culture of learning, experimentation and accountable delivery.

Requirements Summary

Bachelor’s or Master’s degree in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, Engineering or a related discipline, or equivalent practical experience. Typically,

Technical Tools

Data ScienceData & AI

As pioneering innovators for over 100 years, we’re now transforming our organisation to be faster, simpler and more connected. Because we want to be even better equipped to develop digital solutions and experiences that help more people live Healthier, Longer, Better Lives.

To get there, we need people with tech/digital/analytics expertise and passion to help develop positive, sustainable change through digitally enhanced experiences that will impact the lives of millions of people and create a healthier future for everyone.

About the Role

~1 min read

Lead a high-performing Data Science & AI team that turns complex insurance opportunities into trusted, scalable and measurable AI solutions. The role combines people leadership, technology strategy, hands-on technical direction and production accountability across predictive analytics, Generative AI and Agentic AI.

This is a leadership role for someone who enjoys building both people and products. You will shape the Data Science & AI roadmap, coach specialists, stay close enough to the technology to challenge designs and guide delivery, and partner across the organisation to move solutions from idea to sustained business adoption. Your work can support better customer engagement, more efficient operations, stronger risk management and more informed decisions across the life insurance value chain.

Responsibilities

~1 min read

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Build, lead, coach and retain a diverse team of data scientists and AI engineers, creating clear standards, career pathways and a culture of learning, experimentation and accountable delivery.

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Own the unit strategy, capability roadmap and delivery portfolio for advanced analytics, machine learning, Generative AI and Agentic AI, aligned to business priorities and enterprise architecture.

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Translate business needs into responsible AI products with measurable outcomes, from discovery and prototyping through production deployment, adoption, monitoring and continuous improvement.

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Create durable partnerships with business users, Technology, Architecture, Cybersecurity, Data, Risk, Compliance, Group Office, external partners and vendors.

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Ensure every production solution has the governance, documentation, operating model and support structure required for reliable and sustainable use.

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Initiate collection of new data and the refinement of existing data sources with the Data Modelling team if new data is required for AI model development

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Possess strong stakeholder management and communication skills with experience working with senior leadership team / EXCO members.

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Collaborate with potential partner(s) / vendor(s) or internal teams to develop an efficient prototype, conduct assessment of the AI solution, give feedback, determine areas of improvement and finalize the design, to automate or streamline operations within the Company.

Requirements

~1 min read

Bachelor’s or Master’s degree in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, Engineering or a related discipline, or equivalent practical experience.

Typically, 10+ years of relevant experience across data science, machine learning, AI engineering or advanced analytics, including meaningful experience leading and developing technical teams.

Demonstrated delivery of AI or analytics products from problem framing and prototyping through production, adoption and ongoing support.

Strong applied knowledge of Python and SQL. Ability to review solution designs, code, experiments and evaluation results, and to guide technical decisions without needing to be the primary developer for every solution.

Current understanding of modern GenAI architecture, including LLMs or SLMs, RAG, vector search, chatbot or copilot design, agentic workflows, evaluation, guardrails and LLMOps.

Experience partnering with enterprise Technology, security, architecture, data and risk functions in a regulated or complex environment.

Executive-level communication, business consulting, prioritisation and stakeholder management skills, with the ability to explain complex AI topics clearly to non-technical audiences.

Commercial and delivery acumen, including vendor management, budgeting, benefits tracking and portfolio trade-offs.

Experience in life insurance, financial services, healthcare or another highly regulated industry.

Knowledge of insurance use cases such as underwriting, claims, fraud or anomaly detection, customer and agent analytics, next-best action, service automation, retention and operational productivity.

Experience with cloud AI and data platforms, lakehouse architecture, distributed processing, APIs, containers and enterprise DevSecOps practices.

Exposure to knowledge graphs, GraphRAG, multimodal models, synthetic data, privacy-enhancing technologies, causal inference, optimisation or digital experimentation.

Relevant professional certifications in cloud, data, AI, architecture, security, agile delivery or service management.

#LI-DNI

Build a career with us as we help our customers and the community live Healthier, Longer, Better Lives.

You must provide all requested information, including Personal Data, to be considered for this career opportunity. Failure to provide such information may influence the processing and outcome of your application. You are responsible for ensuring that the information you submit is accurate and up-to-date.