"Research Fellow, Business Analytics Centre"

Job Description

The NUS Business Analytics Centre (BAC), a joint initiative between NUS Business School and the School of Computing, oversees the Master of Science in Business Analytics (MSBA) (https://msba.nus.edu.sg/) programme, ranked No. 1 in Asia and among the top 10 globally. BAC has established strong partnerships with leading industry players and top academic institutions through collaborative education and real-world projects.

We are seeking an experienced Research Fellow (Data Science Manager) to lead analytics and AI initiatives with industry partners, and to drive the design, development, and commercialization of AI products, with a strong focus on Large Language Models (LLMs) and Agentic AI systems.

This role sits at the intersection of advanced AI research, real-world business impact, and product development. You will work closely with industry and academic stakeholders, and translate cutting-edge AI capabilities into deployable, scalable solutions.

Duties and Responsibilities

1. Industry & Project Leadership

• Lead end-to-end analytics and AI projects with industry partners, from problem formulation to delivery and deployment.
• Act as the primary technical lead interfacing with business stakeholders, domain experts, and clients.
• Translate business needs into AI system designs, data strategies, and measurable outcomes.
• Ensure projects are delivered on time, within scope, and with high technical and professional standards.

2. LLM & Agentic AI Development

• Design and implement LLM-powered solutions, including:
  • Retrieval-Augmented Generation (RAG)
  • Tool-using and multi-agent systems
  • Workflow orchestration and planning agents
• Lead development of agentic AI architectures for enterprise and industry use cases.
• Evaluate, fine-tune, and deploy foundation models (open-source and commercial).
• Ensure robustness, scalability, safety, and cost efficiency of AI systems.

3. AI Product Development & Commercialization

• Drive the transformation of AI prototypes into production-ready commercial products.
• Collaborate with product, engineering, and business teams on:
  • Product roadmaps
  • Feature prioritization
  • MVP and iteration cycles
• Support go-to-market activities by contributing to technical positioning, demos, and client engagements.
• Identify opportunities for new AI-enabled products and services.

4. Team & Capability Building

• Lead and mentor data scientists, AI engineers, and project teams.
• Establish best practices for:
  • Model development and evaluation
  • MLOps / LLMOps
  • Documentation and reproducibility
• Build a strong culture of technical excellence, collaboration, and applied innovation.

Requirements

• PhD degree in a relevant field.
• Demonstrated professional experience in data science, AI, or applied machine learning.
• Experience leading projects, initiatives, or teams, with responsibility for planning and delivery.
• Strong hands-on experience with:
  • Python and modern ML/AI frameworks
  • LLM ecosystems (e.g. OpenAI, Anthropic, open-source models)
  • Prompt engineering, RAG pipelines, and agent frameworks
• Track record of delivering industry-facing or applied AI solutions.
• Strong communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders.

Additional Qualifications

• Experience with Agentic AI frameworks (e.g. AutoGPT-style systems, CrewAI-like orchestration, custom agent pipelines).
• Familiarity with cloud platforms (AWS, Azure, GCP) and deployment workflows.
• Experience in MLOps / LLMOps, monitoring, and cost optimization.
• Background in consulting, industry partnerships, or enterprise AI delivery.
• Exposure to data governance, AI ethics, or trustworthy AI is a plus.