Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in our team to partner with the Business to provide a comprehensive view.
As a Quantitative Research Associate - Asset and Wealth Management Risk in the Asset & Wealth Management Risk Team, you will be a key member of a diverse and innovative group of quantitative and market risk professionals. Your role will involve developing and maintaining risk measurement methodologies, performing analytics calculations, and managing the Asset and Wealth Management Risk System (Newton). This system, which is continuously developed and maintained by our team, is used by both Risk and Front Office stakeholders within the Asset and Wealth Management sector. We are looking for an analyst to join and partner with senior members of our team to embark on a journey of innovation to introduce and scale up data-driven risk analytics solutions through data science and machine learning techniques to transform our operations and business processes, strengthening the core value proposition of our system and expanding flexible analytical capabilities for the growth of Newton’s platform.
Job responsibilities :
•Contribute to the research and enhancement of the risk methodology for AWM Risk Analytics. The methodology covers sensitivity, stress, VaR, factor modeling, and Lending Value pricing for investment (market), counterparty (credit), and liquidity risk.
• Work with peers and stakeholders to identify use cases and opportunities for Data Science to create value. Use your knowledge of Computer Science, Statistics, Mathematics and Data Science techniques to provide further insights into security and portfolio risk analytics.
• Assist with continuous improvements in our adopted Machine Learning and statistical technics used in our data and analytics validation process.
• Collaborate, design, and deliver solutions that are flexible and scalable using the firm’s approved tools.
• Prepare comprehensive model documentation for the Model Risk Governance and Review group to validate the models our team owns and uses, along with ongoing monitoring and back testing.
• Contribute to the analysis of new and large data sets and assist with their onboarding, following our best practice data model and architecture using big data platforms.
Required qualifications, capabilities, and skills :
• 2+ years of experience in a quantitative analysis/research role/ data scientist role within Market/Credit Risk Management, a Front Office role or academic equivalent
• A quantitative, technically proficient individual who is detail-oriented, able to multi-task, and work independently.
• Excellent communication skills.
• A strong understanding of statistics, applied AI/ML techniques, and a practical problem-solving mindset. Practical experience in financial markets in a quantitative analysis/research role within Risk Management, a Front Office role
Preferred qualifications, capabilities, and skills :
• Knowledge of asset pricing, VaR backtesting techniques, and model performance testing is a plus.
• Knowledge in modular programming in SQL, Python, ML, AWS Sagemaker and TensorFlow is preferred.
• A degree in a quantitative or technology field (Economics, Maths/Statistics, Engineering, Computer Science or equivalent) is preferred.