Analyst, Quantitative Risk Analytics

The Analyst, Quantitative Risk Analytics is responsible for applying mathematical, statistical and quantitative finance techniques to measure, analyze and monitor financial risks. The role involves working on market risk and/or credit risk methodologies, models, controls and processes, and contributing to management information and risk analysis of Banking & Treasury portfolios.

Responsibilities

• Produce credit, market or other relevant risk measures and interpretation of the results on a regular basis.
• Participate in projects with guidance from Principal and/or Associate Director, with the aim of improving the Quantitative Risk & Analytics models, methodologies and analytics frameworks.
• Participate in the in-house analytical and exotic pricing library implementation including new scenarios generation models, pricing functions, sensitivities calculation, risk aggregations, PD/LGD modelling.
• Provide advisory pre-trading structuring, collateral mitigants and portfolio what-if analysis for Treasury and Banking.
• Perform portfolio incremental exposure, sensitivities calculation and liquidity haircut calibration.
• Perform the regular market, liquidity and/or credit risks operational processes, including the ICF testing, valuation and perimeter reconciliation, market risk factors parameters estimation, backtesting and impacts analysis on the portfolio exposures.
• Maintain the proprietary reporting layer and in-house Quantitative Risk Engine (QRE) analytics library including the configuration update, release testing, documentation, implementation to address any limitations and/or identified issues.
• Assess and advise on the impact of proposed changes in Bank-wide policies on Risk Management methodologies, models and practices.
• Ensure the timely and accurate production of daily Risk batch including daily perimeter checks, Mark-to-Market (MtM) reconciliation controls, resolution of discrepancies, remediation plans to address any issues and continuous improvement of operational processes.

Requirements

• Master's degree (or equivalent postgraduate qualification) in Quantitative Finance, Mathematics, Statistics, Physics, Engineering, Computer Science or another highly quantitative discipline.
• Some relevant financial industry experience (typically an internship) from an investment or commercial bank, private equity, asset management firm or financial consulting firm operating to international standards.
• Strong knowledge of mathematical finance, probability, statistics, stochastic modelling and numerical methods is essential.
• Practical experience in the implementation or application of quantitative market and/or credit risk measurement methodologies, including areas such as PFE, XVA, VaR, Economic Capital or stress testing.
• Good understanding of all major capital markets instruments across asset classes.
• Good understanding of industry best practices and awareness of regulatory developments in the field of credit and/or market risk.
• Knowledge of industry practices and regulatory developments in the field of market and/or credit risk.
• Strong programming skills in Python and C++.
• Experience in quantitative software development and implementation of financial models is highly desirable.
• Knowledge of quantitative risk analytics, aggregation and reporting platforms (e.g. ActiveViam/Atoti), trading and risk management systems (e.g. Summit), and market data providers (e.g. Bloomberg) would be advantageous.
• Knowledge of devOps, agile development and Git desirable.
• Plans work well, establishes suitable priorities, anticipates problems and responds in a timely manner, meets deadlines.
• Ability to communicate well at all levels, from senior management to portfolio managers/traders, risk managers, accountants, middle office and IT staff.
• Ability to explain quantitative results and model outputs to both technical and non-technical audiences.
• Ability to work to deadlines and under time pressure.
• Understanding of software development lifecycle, version control and testing practices.
• A positive attitude to problem solving, identifying solutions and finding ways to overcome obstacles, if need be, through compromise and consensus building.

Skills

• Quantitative Finance
• Mathematical Finance
• Probability
• Statistics
• Stochastic Modelling
• Numerical Analysis
• Market Risk Measurement
• Credit Risk Measurement
• PFE
• XVA
• VaR
• Economic Capital
• Stress Testing
• Capital Markets Instruments
• Regulatory Compliance
• Python Programming
• C/C++ Programming
• Quantitative Software Development
• Financial Modelling
• Quantitative Risk Analytics
• Risk Aggregation and Reporting
• Trading Systems
• Risk Management Systems
• Market Data Providers
• DevOps Automation
• Agile Development
• Git
• Software Development Lifecycle
• Version Control Systems
• Testing Practices

Languages

English