Research Fellow (Financial Machine Learning)

About Nanyang Business School

Nanyang Business School (NBS) at Nanyang Technological University is a leading business school in Asia, known for its strong research in finance, economics, risk management, and data-driven social science. NBS promotes interdisciplinary, policy-relevant research using advanced empirical and computational methods.

The Research Fellow will be based at NBS and will support the school’s research mission by conducting high-quality, original research in the field of Machine Learning in Finance under the supervision of Professor William Cong. The role contributes to the University’s objective of strengthening its global research profile through rigorous empirical work, innovative methodological approaches, and impactful publications.

The successful candidate is expected to further the research agenda aimed at leveraging modern machine learning techniques and advanced econometric methods to address central questions in asset pricing and corporate finance. The role involves developing/ initiating quantitative and data-driven research projects, collaborating with faculty members, presenting research at conferences and seminars, and publishing in leading academic journals.

Responsibilities:

• Conducting high-quality empirical research in Machine Learning in Finance.

• Developing and applying advanced quantitative and econometric methods, including the use of large-scale administrative data, machine learning and natural language processing techniques.

• Advance an ongoing project actively developing.

• Initiate one or two additional collaborative research projects aligned with the broader agenda and collaborate with relevant faculty members.

• Preparing research manuscripts for submission to leading international academic journals.

• Presenting research findings at academic conferences, seminars, and internal workshops.

• Supporting the effective management of research projects, including meeting milestones and maintaining high academic standards.

Key Requirements

• Ph.D. in Finance, Economics, Risk Management, Insurance, Statistics, or a closely related discipline from a reputable institution.

• Demonstrate strong empirical research skills, with experience in applied econometrics and quantitative analysis.

• Show proficiency in working with large-scale datasets, including administrative, textual, or unstructured data.

• Have experience with programming and statistical software commonly used in empirical research (e.g., Python, R, Stata, MATLAB).

• Possess a strong research track record or clear potential for publications in high-quality academic journals.

• Demonstrate the ability to work independently and collaboratively in a research-intensive environment.

• Exhibit strong written and verbal communication skills.

Interested applicants are invited to submit a cover letter, full CV and contact details of two referees/statement of research interest all in one document.

We regret to inform that only shortlisted candidates will be notified.