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Goldman Sachs

Advises on mergers and trades stocks and bonds

Core Engineering Quantitative Engineer Associate / Vice President

Quantitative RiskUpdated on Nov 14
Full-timeLondon, UKNo salary listedIn-person

About the Job

Requirements

  • Excellent academic background in a quantitative field such as mathematics, physics, statistics, economics, engineering, or computer science.
  • Strong programming skills in an object-oriented or functional paradigm, such as Python, C++, or Java.
  • Proven experience in a quantitative finance role, with a strong focus on asset liability management, funding modelling, behavioural modelling, or balance sheet management.
  • Solid understanding of fixed income instruments, interest rate derivatives, curve construction methodologies, pricing and hedging strategies, and their application to balance sheet risk management.
  • Deep understanding of statistical and econometric modelling techniques, such as regression analysis, time-series forecasting, and survival analysis, applied to financial products.
  • Excellent written and verbal communication skills, with the ability to explain complex quantitative concepts to non-technical stakeholders.
  • Ability to work independently and effectively in a collaborative global team environment.

Responsibilities

  • Design, implement, and maintain quantitative models, tools, and frameworks for asset liability management, including net interest margin forecasting, earnings-at-risk, and funding cost projections, to optimize resources.
  • Develop stress and scenario analysis frameworks across portfolios, products, and legal entities to assess performance under market scenarios and identify and quantify key risk exposures, concentration risks, convexity effects, and potential vulnerabilities.
  • Develop and enhance behavioural models for deposits and other channels, including non-maturity deposit modelling, deposit beta estimation, repricing lags, and volume flow projections under different macro scenarios and interest rate environments.
  • Establish backtesting, model performance monitoring, and data quality frameworks to evaluate model accuracy, identify potential drift, and refine behavioural and forecasting assumptions.
  • Develop and uplift models to reflect evolving business needs, maintain model documentation and implementation, and support regulatory inquiries and second-line model validation.
  • Deliver clear presentations and explanations related to balance sheet management for discussion with senior managers, committees, and key stakeholders.

Desired Qualifications

  • A master's degree or PhD is preferred.
  • Experience using AI-based tools in development is a plus.

About the Company

Goldman Sachs

Advises on mergers and trades stocks and bonds

Goldman Sachs advises companies and governments on mergers, raises money for them by selling their stocks and bonds, and trades securities for big investors such as hedge funds and pension funds. It led Ford Motor's 1956 stock market debut, then the largest share sale in US history. Traders buy and sell stocks, bonds, currencies, and commodities for clients and lend them money, while bankers earn a fee on each deal they advise on or arrange. Its asset and wealth management arm invests for institutions and wealthy families and charges fees based on the money it oversees. The firm was founded in 1869, when it began brokering short-term IOUs for New York merchants, and it is based in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1869

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