Global Markets, Quantitative Volatility Trading, Research Strat, Vice President/ Associate
Type: Full Time
Internal Number: 14701347
Divisional Overview Goldman Sachs' Strats business unit is a world leader in developing quantitative and technological solutions to solve complex business problems. Working within the firm's trading, sales, banking and investment management divisions, Strats use their mathematical and scientific training to create financial products, advise clients on transactions, measure risk, and identify market opportunities. Securities Strats play important roles in several areas. Some Strats sit on trading desks, creating cutting-edge derivative pricing models and developing empirical models to provide insight into market behavior. Others develop automated trading algorithms for the firm and its clients, taking an active part in the increasing shift from voice to electronic trading. A third group works directly with the firm's sales force and clients, analyzing exposures, structuring transactions, and applying quantitative concepts to meet client needs. Between these teams, Core Strats design and develop complex parallel computing architectures, electronic trading tool and advanced algorithms. Job Summary and Responsibilities We are looking for a highly motivated professional to join Quantitative Volatility Trading (QVT) within the Equities Franchise. As a Research Strat within QVT you will engage in advanced research and modelling related to pricing, risk management and signal generation, all in the context of a low-latency derivative market making group. Key Responsibilities:
Research alpha on horizons spanning microseconds to days and weeks.
Analyze large sets of data using advanced statistical techniques.
Develop and deploy models for managing risk in a large portfolio of options, warrants/cbbcs, futures and stocks.
Analyze trades and positions, investigate market microstructures, and develop algorithms to maximize trading profitability.
Develop, extend and maintain complex derivatives pricing models .
Strong academic background in a relevant field (e.g. Physics, Mathematics/Statistics, Engineering, or Computer science).
Strong quantitative, problem solving and programming skills.
Strong time management skills with attention to details, and the ability to multi-task.
Strong written and verbal communication skills and ability to work in a collaborative environment.
Relevant work experiences in derivatives.
Experience in high-frequency or algorithmic trading.
Experience in portfolio risk management.
Solid work ethics, team oriented, high levels of motivation.
Ability to work in high-pressure and time-sensitive situations.
Keen sense for recognizing and minimizing operational risks.