Corporate Treasury - London - Associate - Quantitative Engineering

Goldman Sachs
London
2 months ago
Applications closed

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In Corporate Treasury (CT) Engineering, you'll find an exciting confluence of computer science, finance, and mathematics being used to solve for what our shareholders would like from us - a high return for the right risk taken.
Corporate Treasury lies at the heart of Goldman Sachs, ensuring all the businesses have the appropriate level of funding to conduct their activities, while also optimizing the firm's liquidity and managing its risk.
The mission statement of the Interest Rate Risk (IRR) and Analytics Strats team within CT is to develop quantitative models for Asset Liability Management to optimize, analyze, and manage the Firm's interest rate income generated from our assets and interest rate expense incurred on our liabilities.
As part of the team you will be involved in capital markets and banking initiatives, new business activities, and firmwide strategic programs.
Responsibilities:

  • Develop quantitative models for interest rate risk, from both economic and earnings perspectives, liquidity & currency risks.
  • Optimize the firm's interest rate income by developing balance sheet analytics and hedging strategies under various market environments.
  • Understand business needs, data requirements, and specifications; facilitate and develop process workflow required to support implementation of engineering solutions.
  • Perform quantitative analysis and facilitate business understanding of technical results.
  • Work with other Strats and technology departments to optimally leverage financial resources to achieve commercial priorities.

Basic Qualifications:

  • Advanced degrees (PhD or Masters) in quantitative field such as Engineering, Mathematics or Physics -- or Bachelors with relevant work experience.
  • Strong analytical, mathematical and programming background.
  • Expertise in Python, or similar language; experience in software development, including a clear understanding of data structures, algorithms, software design and core programming concepts.
  • Expertise in an aspect of quantitative analysis, e.g. mathematics, physics, statistics, stochastic calculus, scientific computing, econometrics, machine learning algorithms, financial modeling.
  • Experience with financial markets and assets; preference for vanilla interest rate derivative pricing, bond and deposit pricing, curve construction, hedging strategies and risk management.
  • Excellent communication skills, including experience speaking to both technical and business audiences and working globally across multiple regions.

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