Research Associate in Machine Learning and Artificial Intelligence (ML/AI)

Research Associate in Machine Learning and Artificial Intelligence (ML/AI)

Location: SPECIALTY RESEARCH INST/CTRS, Kent Ridge Campus, SG

Company: National University of Singapore

The Role

The Sustainable and Green Finance Institute (SGFIN) is a new university-level research institute in the National University of Singapore (NUS), jointly supported by the Monetary Authority of Singapore (MAS) and NUS. SGFIN aspires to develop deep research capabilities in sustainable and green finance, provide thought leadership in the sustainability space, and shape sustainability outcomes across the financial sector and the economy at large.

This role is ideally suited for those wishing to work in academic or industry research in quantitative analysis, particularly in the area of machine learning and artificial intelligence. The responsibilities of the role will include designing and developing various analytical frameworks to analyze structured, unstructured, and non-traditional data related to corporate financial, environmental, and social indicators.

There are no teaching obligations for this position, and the candidate will have the opportunity to develop their research portfolio.

Duties and Responsibilities

The successful candidate will be expected to assume the following responsibilities:

• Design research projects in close collaboration with the Institute’s Directors (Prof. Sumit Agarwal / A.Prof Johan Sulaeman / A.Prof Zhang Weina) and Research Affiliates.
• Take ownership and responsibility for the successful delivery of research projects, ensuring they are completed within the required deadline and allocated budget, and meeting/exceeding project specifications and targets.
• Participate in pre-project activities such as identifying required resources to ensure project completion including staffing and organizational needs of the project team, and preparing high-level project plans with project timeline and resource requirements.
• Development of data analysis frameworks.
• Plan, supervise, and perform (if necessary) the development of supervised and unsupervised machine learning tools to process information from various data sources, including commercial databases and alternative, non-traditional datasets.
• Plan, supervise, and perform (if necessary) the generation of impact measures using machine learning, in collaboration with the Institute’s Directors and other Research Fellows.
• Monitor progress of research projects and provide necessary interventions to ensure smooth completion of each project.
• Manage and coordinate project deliverables, ensuring their quality.
• Manage industry partners’ expectations by understanding their needs and providing realistic expectations and scope of each project.
• Manage the collaborations with research and industry stakeholders, including providing periodic progress updates and deliverables for grant funding body or project sponsors.
• Preparation of results for industry communications, presentations, and academic articles for journal publications.
• Guide, mentor, and supervise research associates on the project team.
• Work closely with the rest of the SGFIN team to support SGFIN’s activities and objectives.

Requirements

• Academic background in the following subjects is preferred: computing, information systems, economics, business, finance, or related disciplines. A bachelor’s degree is required, a master’s degree in one of these subjects is preferred, with a PhD degree required for the Research Fellow position.
• Basic understanding of the financial sector (banks and other financial institutions), financial markets, corporate financial statements, and credit risk analysis is preferred.
• A thorough knowledge of the research field of machine learning and artificial intelligence is highly preferred.
• Programming skills, including knowledge of machine learning and artificial intelligence processes and tools, are highly desired, along with experience in conducting and supporting research and data analysis of research projects.
• Proactive in problem solving.
• Good time management and planning skills with a commitment to delivery.
• Strong project management skills, with the ability to manage several projects concurrently.
• Strong delivery management experience, with proven track records in managing and steering projects towards smooth execution and on-time delivery.
• Adaptive to change with a positive work attitude.
• Enthusiastic team player who is self-driven, committed, and willing to take initiative.
• Strong interpersonal and leadership skills, effective in coordinating stakeholders, fostering teamwork, and leading high-performance project teams.
• Strong verbal and interpersonal communication skills, along with written communication skills.