Are you passionate about high-performance scientific computing? Do you want to participate in the creation of the next generation of pricing and structuring tools? We are looking for a computational scientist to join our Core Quant Strats team and help us change the way financial products are structured, priced and risk managed at Goldman Sachs.
The core value of the Securities Division is building strong relationships with our institutional clients, which include corporations, financial service providers, and fund managers. We help them buy and sell financial products on exchanges around the world, raise funding, and manage risk. This is a dynamic, entrepreneurial team with a passion for the markets, with individuals who thrive in fast-paced, changing environments and are energized by a bustling trading floor.
The Core Quant Strats team oversees the creation and development of the Securities Division quantitative platform, building the key components which allow us to evaluate the prices of financial products. We aim to develop these tools to be more efficient and precise, whilst also making them directly available to our business users, hence allowing the firm to quickly respond to client needs.
HOW YOU WILL FULFILL YOUR POTENTIAL
Participate in the creation of our brand new pricing platform. Write code which is used to evaluate millions of prices every day.
Partner with structurers, traders and other engineers to build a framework allowing us to develop new financial products more efficiently and calculate risk and price estimates on the fly.
Impact our business by improving our ability to serve our clients and by directly reducing compute cost through more efficient algorithms.
Coordinate the analysis, troubleshooting, and resolution of issues in our software and the broader infrastructure.
SKILLS & EXPERIENCE WE’RE LOOKING FOR
Bachelors, Masters, or PhD in Mathematics, Physics, Computer Science, Engineering or similar subject.
Strong quantitative skills.
Strong programming skills, including clear understanding of algorithms and data structures.
Knowledge of high-performance numerical methods.
Strong interpersonal, communication and presentation skills, both written and verbal.
Comfortable managing multiple stakeholders, driving consensus and influencing outcomes.
Experience building tools and payoff languages used by traders and structurers.
Knowledge of financial derivative pricing.
Experience using a functional programming language: Haskell, OCaml, ML, Scala, F#, etc.
Experience creating and using Domain Specific Languages.
Experience with the Python and/or JVM ecosystem.
Experience working with large distributed systems and multi-threaded applications.
Knowledge of GPU programming.
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