Goldman Sachs Electronic Trading (GSET) is seeking a Quantitative Execution Consultant to join our Equities Execution Solutions & Product 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 and GSET product.

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 Research & Development team to optimize client algorithm/SOR execution quality.

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.
• Backtest, calibrate and optimize existing and new U.S. client trading flows on the proprietary Goldman Sachs trading platform.
• Propose and implement A/B testing methodologies to optimize execution quality.
• Develop and maintain statistical tools for analyzing trading strategy performance.

Basic Qualifications:

• Bachelor’s or Master’s degree in a quantitative field such as Mathematics, Statistics, Computer Science, or Engineering.
• Minimum 1 year of experience in coding and statistical analyses.
• 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.
• Must be willing to work with proprietary technologies.
• Excellent communication and interpersonal skills.

Preferred Qualifications:

• Experience in the financial industry, with some knowledge of algorithmic trading, electronic trading mechanics, HFT strategies, and market microstructure.
• Proficiency in statistical techniques Experience with KDB+ is a plus.