Data Engineer for NUS AIDF CRI Team
Pubblicato il 21-08-2026 - Credit Research Initiative (CRI) in Aosta
ppThe Credit Research Initiative (CRI) team is a world leader in studying and applying the modern data analytics and conventional economic/financial models to credit risk analysis. We invite Ph.D. candidates/holders from quantitative disciplines to apply for the Research Fellowship. /p pThe CRI is committed to achieving academic excellence and practical relevance. It was launched after the financial crisis and premised upon the concept of credit ratings as a public good. Over the course of its developments, it has produced top-tier original research and has helped a wide range of financial institutions, supranational organizations and FinTech companies to solve real-world problems. In collaboration with the International Monetary Fund (IMF), the CRI has developed an automated stress-testing tool based on the CRI PD system – the Bottom-up Default Analysis (BuDA) toolkit. Together with a Singapore-based FinTech company, our technology is extended to help build its credit rating system for Small and Medium-sized Enterprises (SMEs). The CRI team joins the Asian Institute of Digital Finance in NUS in 2020 and currently actively pursues a research project on Natural Language Processing (NLP) to extract credit-focused sentiments in media to complement the structured financial and behavioural data. Looking into the future, the CRI will continue to make the most of data analytics, further automate the system and make the products more actionable for various users. /p h3Responsibilities (include But Not Limited To)
/h3 ulliConducting individual research for journal publications on credit risk management, data analytics, natural language processing, machine learning, deep learning, financial modelling, finance/economics empirical analyses, algorithm development, databases, etc. /liliParticipating in the CRI operations in terms of model development/validation, data production, system enhancement and knowledge dissemination. /liliParticipating in the consulting projects for external parties (e.g. bespoke model development/validation). /li /ul h3Qualification Requirements /h3 ulliExpecting/Holding Ph.D. degree from a quantitative discipline, e.g. Computer Science, Mathematics, Statistics, Physics, Engineering, Operations Research, Marketing, Economics, Finance, etc. The successful candidate is expected to obtain his/her Ph.D. degree at the time of appointment. /liliIntending to do good research and striving to have a real-world impact. /liliWith great curiosity and outstanding ability to learn fast. /liliStrong team spirit and comfortable working with a diverse team in a multi-cultural environment. /liliResponsible and resilient when faced with challenges. /liliExcellent oral and written communication skills. /li /ul h3Application Materials /h3 ulliApplication Form; /liliNUS Personal Data Consent for Job Applicants; /liliA detailed CV including publications; /liliA statement of future research plan and samples of research work; /liliTwo reference letters. /li /ul /p #J-18808-Ljbffr