Lead Data

Overview Implement and deliver advanced data and AI solutions that drive innovation, optimize decision-making, and enhance operational efficiency—contributing directly to the organization's strategic growth and technological leadership. Responsibilities Requirement Analysis & Solution Design: Collaborate with stakeholders to understand business needs, translate requirements into technical specifications, and architect tailored GenAI solutions (e.g., chatbots, content generators) that align with project goals. Development & Deployment of GenAI Models: Develop and deploy generative AI models (e.g., LLMs, GANs) on AWS. Deploy scalable solutions into production environments, ensuring robustness and reliability. Cross-functional Collaboration: Partner with data scientists, software engineers, and business teams to integrate AI capabilities into workflows, ensuring alignment with technical and operational objectives. Data Pipeline Management: Design and maintain efficient data pipelines for preprocessing, cleaning, and augmenting datasets. Ensure data quality, governance, and compliance with privacy regulations. System Integration & API Development: Seamlessly integrate GenAI solutions into existing client infrastructure (e.g., cloud platforms, enterprise systems). Develop APIs and microservices to enable real-time AI functionality. End-to-End GenAI Application Development: Design, develop, and deploy user-facing applications powered by GenAI, including frontend interfaces (e.g., React) and backend services. Integrate AI models into applications to deliver seamless experiences. We are looking for people who AI/ML Engineering 3–5 years of hands-on experience in designing, developing, and deploying machine learning/AI solutions, with 1–2 years focused on generative AI (e.g., LLMs, GANs, diffusion models). Application Development Proven track record in full-stack or backend development, including building and deploying AI-powered applications (e.g., chatbots, content automation tools). Cloud Platforms Experience with cloud services (AWS, Azure, GCP) for AI/ML workflows (e.g., SageMaker, Vertex AI, Azure ML) and infrastructure-as-code (Terraform, CloudFormation). Data Engineering Expertise in building scalable data pipelines (ETL/ELT) using tools like Apache Spark, Airflow, or Databricks. DevOps/MLOps Familiarity with CI/CD pipelines, containerization (Docker, Kubernetes), and model monitoring tools (MLflow). How you succeed Champion and embody our Core Values in everyday tasks and interactions. Demonstrate high level of integrity and accountability. Take initiative to drive improvements and embrace change. Take accountability of business and regulatory compliance risks, implementing measures to mitigate them effectively. Keep abreast with industry trends, regulatory compliance, and emerging threats and technologies to understand and highlight potential concerns/ risks to safeguard our company proactively. Who we are Founded in 1908, Great Eastern is a well-established market leader and trusted brand in Singapore and Malaysia. With over S$100 billion in assets and more than 16 million policyholders, including 12.5 million from government schemes, it provides insurance solutions to customers through three successful distribution channels – a tied agency force, bancassurance, and financial advisory firm Great Eastern Financial Advisers. The Group also operates in Indonesia and Brunei. The Great Eastern Life Assurance Company Limited and Great Eastern General Insurance Limited have been assigned the financial strength and counterparty credit ratings of "AA-" by S&P Global Ratings since 2010, one of the highest among Asian life insurance companies. Great Eastern's asset management subsidiary, Lion Global Investors Limited, is one of the leading asset management companies in Southeast Asia. Great Eastern is a subsidiary of OCBC, the longest established Singapore