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Systematic ETF Trader (Vice President)
150 000 - 300 000$
Описание вакансии
Текст:
TL;DR
Systematic ETF Trader (Vice President): Developing, testing, and executing systematic trading strategies for ETFs across global markets with an accent on algorithmic execution and quantitative modeling. Focus on designing robust backtesting frameworks, managing market risk, and leveraging advanced data analysis to optimize trading performance.
Location: Must be based in New York, NY, United States
Salary: $150,000–$300,000
Company
A leading global investment banking, securities, and investment management firm.
What you will do
- Design and implement algorithmic trading strategies for ETFs across global markets.
- Utilize historical and real-time data to build predictive models for trading decisions.
- Conduct rigorous backtesting to ensure strategy robustness and optimize risk-adjusted returns.
- Manage and execute trades via automated systems while minimizing slippage and market impact.
- Monitor market, liquidity, and operational risks to ensure compliance with firm guidelines.
- Collaborate with quantitative researchers and data scientists to refine and improve strategy performance.
Requirements
- Bachelor's degree in Finance, Economics, Engineering, Computer Science, Mathematics, or a related field.
- Minimum 2+ years of experience as a quantitative or systematic trader with a focus on ETFs.
- Proficiency in programming languages such as Python, C++, or Java.
- Strong background in statistics, econometrics, or machine learning.
- Deep understanding of financial markets, ETF structure, and market microstructure.
- Strong analytical and critical thinking skills with the ability to adapt to evolving market conditions.
Culture & Benefits
- Opportunity to work in a dynamic, high-performance trading environment.
- Access to advanced tools and platforms for financial modeling and execution.
- Eligibility for a discretionary bonus based on performance and fiscal year-end status.
- Collaboration with world-class quantitative researchers and data scientists.
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