About the position
Goldman Sachs Quantitative Engineering is a leading developer of quantitative models and cutting edge systems to solve complex business problems. Working with the firm's trading, operations, finance, sales, banking and investing businesses, engineers use their mathematical and scientific training to create financial products, advise clients on transactions, identify market opportunities, assist managing risks, and provide technical solutions to facilitate all business activities. Goldman Sachs Asset and Wealth Management Division (AWM) is one of the key revenue generating Divisions of the Firm. AWM Alternatives is the private side of Asset Management and invests in a wide range of global asset classes including: Private Credit, Real Estate, Corporate Private Equity, Growth Equity and Infrastructure worldwide. The AM Private Alternatives Strategists collaborate with investing and finance professionals to create quantitative computer models and web applications to support all aspects of the investing and lending life cycle. We create quantitative models and develop software applications to help structure, value, hedge, and risk manage the investments in our portfolios, and applications as an interface to those models. Members hold advanced degrees in Engineering, Computer Science, Mathematics and Physics. The team proactively collaborates with colleagues globally to ensure that the best solutions are implemented.
Responsibilities
- Develop and implement quantitative models and algorithms to support risk management and investment strategies
- Conduct statistical and mathematical analysis of financial data to identify patterns and trends
- Collaborate with portfolio & fund managers to identify areas where quantitative analysis can provide insights and support decision-making
- Lead the development of proprietary models and algorithms to support the company's risk management and investment strategies
- Communicate results and findings to stakeholders in a clear and concise manner
- Stay current with industry developments and new technologies
Requirements
- Advanced degree in a related field such as Mathematics, Physics, Computer Science, Financial Engineering or a related field.
- Strong programming skills in at least one language such as Python, R, C++ or Java
- Strong understanding of mathematical and statistical concepts, especially in finance
- Strong problem-solving skills and the ability to think critically
- Excellent communication skills and the ability to work well in a team environment
- Strong experience in financial markets, risk management and time series analysis.
- Working knowledge of Corporate Finance and Financing Mathematics
