Global Banking & Markets, Equities Execution Consultancy, Associate/Vice President, Hong Kong

Goldman Sachs Electronic Trading (GSET) is seeking a highly skilled Quantitative Execution Consultant to join our Equities Execution Consultancy team, focusing on Asia Equities markets. This role requires a strong understanding of algorithmic trading, market microstructure, and statistical analysis, with the ability to translate quantitative insights into actionable recommendations for our clients.

As a member of our team, you will be responsible for conducting in-depth analysis of client execution performance, utilizing transaction cost models (TCM) and statistical testing methodologies. You will present your findings to clients and collaborate with the GSET algorithm team to customize algorithm behavior to optimize execution quality across execution algorithms and smart order routers.

Our team consists of experienced client-facing programmers and quants who are passionate about leveraging data-driven insights to enhance client performance. The team sits on the trading floor and has direct relationships with our major clients.

Responsibilities:

• Discuss execution performance with clients, traders, sales, and compliance.
• Develop and maintain a deep understanding of client performance benchmarks and implement strategies for continuous improvement.
• Apply transaction cost models and analyze the impact of market microstructure on execution performance.
• Evaluate and leverage various liquidity options to optimize client execution strategies.
• Develop and maintain statistical software and tools for analyzing trading strategy performance.
• Design and implement trading simulations for algorithm parameterization and optimization.
• Implement A/B testing methodologies to optimize algorithm parameters based on statistical significance.

Basic Qualifications:

• Bachelor’s or Master’s degree in a quantitative field such as Mathematics, Statistics, Computer Science, or Engineering.
• Minimum 2 years of experience in coding, with a strong command of Python programming, including experience with data analysis libraries (e.g., Pandas, NumPy, SciPy).
• Strong understanding of parametric and non-parametric statistical tests, including hypothesis testing, regression analysis, and time series analysis.
• Proficiency in data visualization techniques and tools.
• Excellent communication and interpersonal skills.

Preferred Qualifications:

• Experience in the financial industry, with specific knowledge of algorithmic trading, electronic trading mechanics, HFT strategies, and market microstructure.
• Proficiency in statistical and machine-learning modules for Python (e.g., scikit-learn, statsmodels). Experience with KDB+ is a plus.
• Prior experience in a client-facing role involving technical consulting or sales.

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Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.