Job Description
The Asian Institute of Digital Finance (AIDF) is a university-level institute at the National University of Singapore (NUS), jointly founded by the Monetary Authority of Singapore (MAS), the National Research Foundation (NRF) and NUS. AIDF aspires to be at the forefront of research-driven Fintech innovation in Singapore by acting as an experimental site for developing digital financial technologies, as well as nurturing current and future Fintech researchers and practitioners in Asia.
The Credit Research Initiative (CRI), one of the flagship research initiatives under AIDF, is a non-profit undertaking founded in 2009. Pioneering the "public good" credit risk measure, the initiative is committed to advancing big data analytics and providing directly useful credit intelligence to academic and professional communities. Our clients include international regulatory authorities (such as the IMF and MAS) and multinational financial institutions around the world.
An exciting opportunity exists to join NUS-AIDF as a Research Analyst under different teams involved with big-data analytics. You will participate in the production of our data products and contribute to the ongoing research and development of the flagship NUS-CRI Probability of Default model. This opportunity will challenge successful applicants and is a great learning and development opportunity for those interested in finance and risk management.
Career Benefits
- Gain a detailed understanding of a cutting-edge quantitative credit risk model.
- Further your knowledge in data engineering, quantitative modeling and financial analysis.
- Involve yourself in emerging technologies (e.g. cloud/grid computing, GPU computing) in the Fintech field.
- Benefit from a world-class research environment at the forefront of credit risk, with a motivated research team and a well-established network spanning across a multitude of industries.
- Opportunities to interact with and learn from financial and tech professionals, industry experts, and thought leaders.
Requirements
- Fundamental quantitative skills, preferably those obtained during a bachelor’s degree in mathematics, computer science, economics, finance etc.
- Good programming skills (Julia, Python, Matlab, SQL, etc.) or financial fundamentals are ideal
- Good team player with strong sense of responsibility and strong communication skills
- Highly self-motivated
- Willing to learn new technical skills