AI & Analytics Developer

About the Role

We are seeking a Senior AI & Analytics Developer to join a dynamic Data & Analytics team based in Singapore. The role involves designing, building, and deploying analytics and AI solutions that enhance innovation and deliver business value. This position requires strong software engineering skills to develop scalable, production-ready machine learning models, APIs, and data-driven applications.

Key Responsibilities

• Design, develop, and maintain end-to-end AI and analytics solutions in collaboration with cross-functional teams.
• Write high-quality, maintainable, and well-documented code adhering to best software engineering standards, including version control and automated testing.
• Develop and optimize data pipelines, ensuring efficient and secure integration from varied sources.
• Build intelligent, API-driven AI services for diverse business use cases using Python and modern AI frameworks.
• Utilize tools and libraries like Pandas and Pydantic for building robust data pipelines; deploy advanced AI workflow automation technologies.
• Create user interfaces employing contemporary web technologies such as JavaScript or TypeScript and frameworks for frontend and backend development.
• Implement machine learning and analytics solutions with monitoring for model performance, data drift, and system observability.
• Manage deployment using containerization and workflow orchestration tools.
• Integrate services with cloud platforms and develop microservices architectures with scalable RESTful or GraphQL APIs.
• Ensure solutions comply with security, privacy, and responsible AI standards.
• Keep up-to-date with trends and best practices in AI, analytics, and software development.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or related fields.
• Strong problem-solving ability and capability to communicate technical information to non-technical stakeholders.
• Proficient in software engineering principles and experienced with multiple programming languages such as Python, Java, or JavaScript.
• Hands-on experience with AI/ML frameworks and building production-grade data pipelines following DataOps and MLOps practices.
• Familiarity with containerization (Docker, Kubernetes) and CI/CD pipeline automation.
• Experience with modern web development and building scalable APIs.
• Knowledge of cloud platforms (preferred but not specific).
• Understanding of security, privacy, and regulatory compliance within AI/ML contexts.
• Prior exposure to regulated industries or financial services is a plus.
• Comfortable using data visualization and team collaboration tools.