AIA Malaysia Hiring! Full Time Data Science, Principal in Federal Territory - Ricebowl

Position Objective:

To establish and advance Data Science and Artificial Intelligence capabilities that enable data-driven decision-making and support AIA's purpose of helping people live Healthier, Longer, Better Lives.

Act as the technical leader and subject matter expert in Data Science, Machine Learning, and Generative AI by designing and delivering innovative analytics solutions that drive business growth, enhance customer experience, improve operational efficiency, and generate measurable business value.

Partner closely with business stakeholders, the Insights team, and technology partners to shape the analytics roadmap, promote best practices, and develop scalable solutions that strengthen enterprise analytical capabilities and can be replicated across AIA markets.

Roles and Responsibilities:

Data Science Leadership & Advisory

• Serve as the principal technical expert in Data Science, Machine Learning, and Artificial Intelligence, providing thought leadership and guidance across the organization.
• Partner with business stakeholders and the Insights team to identify opportunities where analytics and AI can create measurable business value.
• Translate complex business challenges into actionable analytics strategies, models, and solutions.
• Provide technical consultation and recommendations to stakeholders on analytical approaches, methodologies, and emerging technologies.

Advanced Analytics & Machine Learning

• Design, develop, and deploy advanced analytics solutions utilizing large and complex datasets to support business growth, operational efficiency, customer experience, and strategic decision-making.
• Apply a broad range of analytical and machine learning techniques, including predictive modelling, propensity modelling, segmentation, clustering, neural networks, hypothesis testing, simulation modelling, and optimization.
• Lead the end-to-end model development lifecycle, from problem definition and feature engineering to validation, deployment, monitoring, and continuous improvement.
• Drive the adoption of best-in-class analytical methodologies and modelling practices.

Generative AI & Emerging Technology Solutions

• Design and implement scalable Generative AI solutions leveraging Large Language Models (LLMs), AI Agents, vector databases, orchestration frameworks, and multimodal AI capabilities.
• Identify, evaluate, and prioritize high-value AI and Generative AI use cases that address business needs and deliver measurable outcomes.
• Develop evaluation frameworks and performance measures to assess solution effectiveness, accuracy, reliability, scalability, and business impact.
• Stay abreast of emerging trends and technological advancements in AI, Machine Learning, and Data Science, and recommend innovative applications to strengthen organizational capabilities.

Solution Development & Innovation

• Collaborate with business stakeholders, technology teams, vendors, and strategic partners to design, prototype, and implement innovative analytics and AI solutions.
• Lead proof-of-concept initiatives and experimentation activities to validate new technologies, methodologies, and business applications.
• Support the acquisition of new data sources and enhancement of existing datasets to improve analytical capabilities and business insights.
• Contribute to the development of reusable frameworks, assets, and best practices that can be adopted across functions and markets.

Governance & Operational Excellence

• Promote and apply best practices in Data Science, MLOps, AI governance, model lifecycle management, and Responsible AI.
• Ensure solutions comply with internal governance standards, regulatory requirements, and ethical AI principles.
• Establish and maintain high-quality technical, procedural, and model documentation to ensure transparency, consistency, and auditability.
• Drive continuous improvement of analytical processes, controls, and delivery practices to enhance effectiveness and scalability.

Stakeholder Collaboration & Capability Building

• Build strong relationships with business stakeholders to promote the adoption and effective use of analytics and AI solutions.
• Communicate complex analytical concepts and findings effectively to both technical and non-technical audiences, including senior leadership and executive stakeholders.
• Mentor and provide technical guidance to data scientists and analytics practitioners, supporting capability development and knowledge sharing across the organization.
• Foster a culture of innovation, continuous learning, and analytical excellence within the broader analytics community.

Minimum Job Requirements:

• Expert in programming based analytics with experience in the following languages:
• SQL (mandatory)
• Python
• LLM prompt engineering
• Proven experience in building statistical models, segmentations, predictive and propensity models (e.g clustering, predictive models, neural network, scenario analysis, conceptual modeling, hypothesis testing).
• Good understanding of machine learning model management and AI principles and practices
• Able to work in a fast-paced, multidisciplinary and competitive environment
• Strong analytical skills, deductive reasoning, problem solving and critical thinking skills
• Able to collaborate with other teams to drive positive outcomes
• Strong business acumen, people management and project management skills to prioritize & manage multiple priorities
• Proven experience designing and implementing solutions using LLMs (e.g. GPT,Gemini), RAG frameworks, vector databases, AI agent frameworks, prompt engineering, and model evaluation methodologies.
• Deep knowledge of Responsible AI principles, AI security, model monitoring, hallucination mitigation, AI governance frameworks, and regulatory considerations, particularly within highly regulated industries such as financial services or insurance.
• Experience in enterprise-scale deployment of GenAI solution (e.g., Azure AI Foundry, Azure OpenAI, Microsoft Copilot Studio, Databricks) including CI/CD, MLOps/LLMOps, observability, performance optimization, and operational support models.
• Strong sense of urgency and accountability to drive business outcomes
• Bachelor's Degree / Masters in relevant fields Required
• 8 years’ experience and above