Quantitative Engineering - Vice President - Global Banking & Markets

Equities Systematic Volatility Trading Strats

In Goldman Sachs quantitative strategists are a the cutting edge of our businesses, solving real-world problems through a variety of analytical methods. Working in close collaboration with traders and sales, strats invaluable quantitative perspectives on complex financial and technical challenges power our business decisions.

We are a team of desk strategists who work to transform the ETFs businesses by automating the key decisions taken every day. Our team has a wide remit including automatic quoting, optimizing hedging decisions and developing algorithms to trade ETFs on venues around the world.  We also deploy statistical analysis techniques and mathematical models to enhance the decision making process, with the overall aim of improving business performance while working closely with traders and salespeople on the trading floor.

Role Responsibilities

• Automate pricing of ETFs, providing fast and accurate prices in response to quote requests from our clients.
• Implement automated hedging algorithms, and build frameworks to manage risk centrally across asset classes.
• Perform systematic and quantitative analysis of franchise flows and market data, driving business decisions and the design of our automation platform.
• Work closely with sales and trading, support our automated pricing and trading systems.
• Be involved with all stages of the software development life cycle with a range of technologies, and collaborate closely with engineering teams who support the underlying infrastructure and frameworks,

Basic Qualifications

• Excellent academic record in a relevant quantitative field such as physics, mathematics, statistics, engineering or computer science.
• Strong analytics stills with experience in quantitative modelling and data analytics.
• 5.5+ years experience.
• Strong programming skills in an object oriented or functional paradigm, with particular strength in Java, Python and its core concepts.
• Self-starter who can work with minimum guidance, ability to manage multiple priorities and work in a high-pressure environment.
• Excellent written and verbal communication skills.

Preferred Qualifications

• Experience implementing data-driven, streaming market making models, working with large scale timeseries and dimensional data.
• Previous quantitative or technical role working on or with a derivatives market making desk (irrespective of asset class),
• Knowledge of building automated trading systems and researching signals for use in a live trading environment. Experience with machine learning is a plus.
• Experience with real-time systems/messaging infrastructures
• Familiarity with build/deployment/runtime tools e.g. Gradle, Maven, Git, Spring, Kubernetes

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