Analyst, Portfolio Risk Management

The Portfolio Risk & Analytics function is one of the eight functions within the Singapore Risk Management organization. Its main role is to produce insights into the credit portfolio of the country, by way of portfolio analyses, deep dives and stress testing, thereby supporting a proactive portfolio management stance in line with risk appetite.

The position reporting directly to the Head of Portfolio Risk Management (PRM) will support the delivery of key activities withinstress testing and portfolio analytics.This includes ensuring data quality in our process, analyzing portfolio structure and movements, coding key calculation routine, reviewing results and testing code changes for the different processes within our Stress Testing team. It also involves supporting the implementation of new processes and activities linked to the portfolio management program.

The typical candidate for this position would have knowledge about SAS and SQL or similar tool coding and aptitude to extract, transform and analyze data. The candidate should be able to have self-drive and keen on learning more about the technical development as well a confident personality with strong technical skills with good written and verbal communication skills would be key for this position.

Job Responsibilities:

• Support in data extraction and credit analysis
• Support in automation of reports and stress test processes through SAS, Python and R
• Contribute in development and enhancements of stress testing and portfolio analytics methodologies
• Develop and revise stress testing code for new methodologies and process
• Support in review and enhancement of stress test policies and procedures
• Conduct UAT to code changes and develop business requirements document (in an agile setting)
• Provide results review and analytics support for the different stress tests performed within Portfolio Risk Management
• Support other Group PRM initiatives in their development and implementation

Requirements:

• Minimum qualification: A degree in Banking & Finance / Economics / Technical Sciences or equivalent training/experience
• Proficient with MS Office applications (including Excel, PowerPoint), data query tools (SAS, SQL, etc.) and high level programming languages (R, Python).
• Proficient in data extraction, transformation and analysis of data
• Knowledge of statistical analysis techniques and financial modeling within the financial services environment would be an added advantage.