Design, develop, and enhance scalable data science solutions and products that support Revenue Growth Management (RGM), translating complex business challenges—including pricing, promotions, trade spend, and customer profitability—into data-driven insights that enable commercial decision-making.
Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.
Own the agentic-evaluation engine. Build the capability that scores agents on the metrics that matter - intent resolution, tool-selection and parameterisation accuracy, task adherence, planning quality, tool-call ordering, response completeness against a reference, and when an agent should defer to a human.
Accelerate your leadership by managing a multidisciplinary team of AI engineers and software developers, improving capability through coaching and structured feedback.
Develop and derive first-principles mathematical models for quantum gravimeters, including dynamic edge cases and approaches based on Feynman paths and optical Bloch equations, where applicable.
Solution Delivery: Work with internal customers to understand business problems, shape feasible AI solution options, validate value through prototypes, and deliver solutions into productive use.
AI solution development: Develop and test LLM-based agentic workflows, retrieval-augmented generation (RAG) pipelines and machine learning models for audit and firm processes. Deliver solutions through well-defined APIs that follow the platform's CI/CD standards, for integration into the firm's central platform.
Work closely with other research team members to research, develop, and integrate AI and XR technologies for railway operations, inspection, maintenance, and training.
As a Data Acquisition Engineer (AI Systems), you will work at the intersection of software engineering, browser automation, distributed systems, and AI. You will help design and build platforms that collect, process, and deliver structured data from a wide range of public sources while continuously improving their reliability and resilience.