AI Scientist - Financial Market Risk and Portfolio Analytics, IHPC

At A*STAR Institute of High Performance Computing (A*STAR IHPC), our team focuses on advanced AI research for real-world financial solutions, translating rigorous scientific innovation into practical, high-impact applications. We develop and deploy AI models, including foundation models, and large language models (LLMs) to address complex challenges in financial market risk quantification, portfolio optimization.

We collaborate closely with fintech companies and corporate banks. Team members gain exposure to the full end-to-end AI lifecycle, from research and prototyping, through rigorous validation, to deployment in production environments, creating strong opportunities for technical growth, ownership, and real-world impact.

We are seeking AI Scientists to join our team. In this role, you will lead the design and development of advanced AI models to enhance predictive accuracy and interpretability in portfolio risk and broader financial risk quantification. You will drive methodological innovation by integrating cutting-edge research with real-world financial data, creating measurable impact on decision-making, risk assessment, and financial strategy.

Requirements

Must-Have Qualifications

• PhD in Computer Science, Quantitative Finance, Statistics or closely related field. 
• Experience with time series foundation modelling, including forecasting, or scenario simulation.
• Strong publication record in top AI/ML conferences or high impact journals.
• Proven experience in financial market risk modelling.

Strong-Plus Qualifications

• Expertise in large language models (LLMs), foundation models.
• Experience in Mark-to-Market modelling.
• Expertise in stress-testing frameworks for financial portfolios.
• Publications, patents, or impactful contributions in quantitative finance.

Key Responsibilities

Research and Development

• Drive the design, development, and experimentation of AI models for financial risk and portfolio analytics.
• Explore novel methodologies to enhance predictive accuracy, interpretability, and generalization in market risk.

Translation and Collaboration

• Collaborate with cross-functional teams, including industry partners to align AI solutions with real-world requirements.
• Communicate complex AI concepts and model results effectively to technical and semi-technical stakeholders, ensuring transparency and trust.

Outcomes and Impacts

• Deliver measurable improvements in financial services, influencing decision-making and risk management strategies.
• Contribute to thought leadership and knowledge creation through publications, patents.