GBM - Public, ETF Trading, Vice President - New York

Goldman Sachs•New York, NY

2d•$150,000 - $300,000•Onsite

About The Position

We are seeking a highly skilled and motivated Systematic ETF Trader to join our dynamic trading team. The ideal candidate will be responsible for developing, testing, and executing systematic trading strategies focused on Exchange-Traded Funds (ETFs) across various asset classes. This is an excellent opportunity for a quantitative professional with a passion for financial markets and algorithmic trading.

Requirements

Bachelor's degree in Finance, Economics, Engineering, Computer Science, Mathematics, or a related field.
Proven experience (2+ years) as a quantitative trader, systematic trader, or similar role, with a strong focus on ETFs and algorithmic trading.
Proficiency in programming languages such as Python, C++, Java, or similar, along with experience in financial modeling, data analysis, and backtesting.
Strong background in statistics, econometrics, or machine learning techniques, with the ability to apply them to trading strategies.
Deep understanding of financial markets, especially ETFs, including structure, liquidity, and market microstructure.
Strong analytical and problem-solving skills with a keen ability to think critically and adapt to evolving market conditions.
Strong verbal and written communication skills for collaborating across teams and presenting findings to stakeholders.

Responsibilities

Design, develop, and implement algorithmic trading strategies that trade ETFs across global markets.
Utilize historical and real-time market data to identify inefficiencies and create predictive models that inform trading decisions.
Conduct rigorous backtesting of trading strategies to ensure robustness and optimize for risk-adjusted returns.
Manage and execute trades through automated systems, ensuring minimal slippage, transaction costs, and market impact.
Monitor and manage trading risks, including market risk, liquidity risk, and operational risk, ensuring compliance with risk guidelines and limits.
Track and analyze the performance of strategies, identify areas for improvement, and implement iterative changes to enhance profitability and performance.
Work closely with quantitative researchers, data scientists, and other traders to refine strategies and improve performance.
Leverage advanced tools and platforms for data analysis, strategy development, and execution (e.g., Python, SQL, MATLAB, etc.).