Research Fellow, Business Analytics Centre
Skills
About the role
Job Title: Research Fellow, Business Analytics Centre
University-Level Unit: School of Business
Faculty/Department-Level Unit: Analytics And Operations
Employee Category: Research Staff
Location_ONB: Kent Ridge Campus
Posting Start Date: 06/02/2026
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.
More Information
Location: Kent Ridge Campus
Organization: School of Business
Department : Analytics And Operations
Employee Referral Eligible: No
Job requisition ID : 31681
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