Risk-LONDON-Associate-Quantitative Engineering London, England
Job description
The Risk division is responsible for credit, market and operational risk, model risk, independent liquidity risk, and insurance throughout the firm.
RISK ENGINEERING
Risk Engineering ("RE"), which is part of the Risk Division, is a central part of the Goldman Sachs risk management framework, with primary responsibility to provide robust metrics, data-driven insights, and effective technologies for risk management. RE is staffed globally with offices including Dallas, New Jersey, New York, Salt Lake City, London, Warsaw, Bengaluru, Singapore, and Tokyo.
LIQUIDITY AND PRIME RISK STRATS
Liquidity and Prime Risk Strats use their engineering and mathematical background to identify and measure risk and to implement quantitative and technical risk modelling solutions. Successful Strats are highly analytical, driven to own commercial outcomes, and communicate with precision and clarity. As a part of the team, you will work with our key business partners and understand financial markets to quantify the firm’s liquidity risk and key risks in prime brokerage business . You will also focus on developing quantitative models & scalable architecture.
RESPONSIBILITIES AND QUALIFICATIONS
- Develop, implement, and maintain quantitative measures of liquidity risk using advanced mathematical/statistical/engineering approaches
- Perform quantitative analysis and facilitate understanding of a variety of financial instruments, including secured funding transactions, collateral firm and client inventory, and loans and commitments
- Quantify and monitor measures of risk in different areas across the firm, such as prime brokerage, synthetic trading, and repo trading
- Work alongside revenue generating functions and corporate treasury to implement the liquidity regulatory requirements
- Communicate clearly complex mathematical concepts with internal and external stakeholders such as risk managers, senior management and regulators.
- Updating and maintaining risk models along with business growth and risk environment changes
- Developing and maintaining large scale risk infrastructures/systems in a compiled or scripting language
QUALIFICATIONS
- Strong quantitative skills with an advanced degree in Mathematics, Physics, Engineering or other highly quantitative discipline
- Strong programming skills and experience with an object oriented programming language (Java, C++ etc.).
- Strong written and verbal communication skills – ability to explain complex quantitative concepts to a non-technical audience
- Strong analytical and problem solving skills using math, statistics, and programming
- PhD and/or Post-doctoral academia experience is welcome
- Familiarity with financial markets, financial assets and liquidity risk is a plus
- Experience working in a quant hedge fund or prime brokerage business is a plus
