Research Analyst in Machine Learning and Artificial Intelligence

National University of Singapore; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading research university in Singapore seeks a candidate for a role within the Sustainable and Green Finance Institute. The successful applicant will engage in innovative research, design analytical frameworks, and develop machine learning tools. A Bachelor's degree is essential, with a Master's preferred, alongside strong problem-solving, project management, and interpersonal skills. In this demanding role, candidates will manage various research projects to influence sustainability across the financial sector.

Qualifications

• Bachelor's degree required; Master's preferred.
• Knowledge of financial sectors and markets is preferred.
• Experience with machine learning and AI processes is highly preferred.

Responsibilities

• Design research projects in collaboration with Institute Directors.
• Manage research project deliverables and monitor their progress.
• Develop data analysis frameworks and machine learning tools.

Skills

Problem solving

Project management

Interpersonal communication

Team collaboration

Time management

Education

Bachelor's degree in computing, information systems, economics, business, or finance

Master's degree in a related field

Tools

Machine learning tools

Programming languages

Database management systems

Job description

Company Description

The National University of Singapore is the national research university of Singapore. Founded in 1905 as the Straits Settlements and the Federated Malay States Government Medical School, NUS the oldest higher education institution in Singapore.

Job Description

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 analyse structure, 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 organisational needs of the project team, and preparing high-level project plans with project timeline and resource requirements
• Contribute to the development of data analysis frameworks
• Contribute to the development of supervised and unsupervised machine learning tools to process information from various data sources, including commercial databases and alternative, non-traditional datasets
• Contribute to the development of impact measures using machine learning, under the direction of the Institute's Directors and 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 the collaborations with research and industry stakeholders, including providing periodic progress updates and deliverables for grant funding body or project sponsors
• Manage industry partners' expectation by understanding their needs and providing realistic expectations and scope of each project
• Work closely with the rest of the SGFIN team to support SGFIN's activities and objectives

Qualifications

• Academic background in the following subjects is preferred: computing, information systems, economics, business, finance, or related disciplines. A bachelor's degree is required, with a master's degree in one of these subjects is preferred.
• Basic understanding of financial sector (banks and other financial institutions), financial markets, corporate financial statements, and credit risk analysis, is preferred.
• 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.
• Database management experience is desired.
• Proactive in problem solving.
• Good time management and planning skills with a commitment to delivery.
• Strong project management skills, with 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 skills, effective in coordinating stakeholders, fostering teamwork, and working in a high performance project team.
• Strong verbal and interpersonal communication skills, along with written communication skills

More Information

Location: Kent Ridge Campus

Organization: Sustainable and Green Finance Institute

Department: Sustainable and Green Finance Institute

Employee Referral Eligible: No

Job requisition ID: 31582