
GBM - Public, ETF Trading, Vice President - New York
About the role
About the Role:
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.
Key Responsibilities:
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Strategy Development:
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Design, develop, and implement algorithmic trading strategies that trade ETFs across global markets.
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Data Analysis & Modeling:
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Utilize historical and real-time market data to identify inefficiencies and create predictive models that inform trading decisions.
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Backtesting & Optimization:
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Conduct rigorous backtesting of trading strategies to ensure robustness and optimize for risk-adjusted returns.
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Execution:
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Manage and execute trades through automated systems, ensuring minimal slippage, transaction costs, and market impact.
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Risk Management:
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Monitor and manage trading risks, including market risk, liquidity risk, and operational risk, ensuring compliance with risk guidelines and limits.
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Performance Analysis:
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Track and analyze the performance of strategies, identify areas for improvement, and implement iterative changes to enhance profitability and performance.
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Collaboration:
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Work closely with quantitative researchers, data scientists, and other traders to refine strategies and improve performance.
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Technology Integration:
Leverage advanced tools and platforms for data analysis, strategy development, and execution (e.g., Python, SQL, MATLAB, etc.).
Requirements:
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Education:
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Bachelor's degree in Finance, Economics, Engineering, Computer Science, Mathematics, or a related field.
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Experience:
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Proven experience (2+ years) as a quantitative trader, systematic trader, or similar role, with a strong focus on ETFs and algorithmic trading.
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Technical Skills:
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Proficiency in programming languages such as Python, C++, Java, or similar, along with experience in financial modeling, data analysis, and backtesting.
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Quantitative Skills:
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Strong background in statistics, econometrics, or machine learning techniques, with the ability to apply them to trading strategies.
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Market Knowledge:
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Deep understanding of financial markets, especially ETFs, including structure, liquidity, and market microstructure.
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Problem-Solving:
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Strong analytical and problem-solving skills with a keen ability to think critically and adapt to evolving market conditions.
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Communication:
Strong verbal and written communication skills for collaborating across teams and presenting findings to stakeholders.
The expected base salary for this New York, New York, United States-based position is $150,000-$300,000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.
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