Our client, a leading global trading firm, is seeking an Execution Trader / Quant to assist one of their leading Portfolio Managers and help grow the desk and maintain their excellent performance through 2024. With a commitment to innovation, cutting-edge technology, and a deep understanding of the Commodities (Ags) markets, they have consistently maintained a prominent position in the industry.
We are seeking a highly skilled and motivated Execution Trader / Quant with a deep market knowledge of the Ags market to join our client's dynamic team. The successful incumbent will play a crucial role in optimizing trading strategies, enhancing risk management processes, and contributing to the firm's overall success in the commodities market.
- Quantitative Modeling: Develop and implement advanced quantitative models for analyzing and predicting price movements, market trends, and risk factors in the agricultural commodities space.
- Algorithmic Trading: Design, test, and optimize algorithmic trading strategies to maximize profitability while managing risk effectively. Collaborate with cross-functional teams to integrate quantitative models into trading systems.
- Market Analysis: Conduct in-depth research on global agricultural markets, staying abreast of relevant economic, geopolitical, and environmental factors that may impact commodity prices. Provide insights and recommendations based on quantitative analysis.
- Risk Management: Work closely with risk management teams to enhance risk models and ensure compliance with risk limits. Develop tools and methodologies for assessing and mitigating trading risks associated with agricultural commodities.
- Execution Strategy: Implement and refine execution strategies to improve trading efficiency and reduce transaction costs. Monitor and optimize trade execution processes to achieve optimal outcomes.
- Data Analysis: Utilize large datasets to extract meaningful insights and identify patterns that can inform trading decisions. Collaborate with data scientists and analysts to continuously enhance data-driven approaches.
- Collaboration: Collaborate with cross-functional teams, including traders, researchers, and technology experts, to integrate quantitative solutions seamlessly into the trading infrastructure.
- Educational Background: Advanced degree in a quantitative field such as Finance, Mathematics, Statistics, or a related discipline.
- Experience: Proven experience working in a quantitative role within the commodities or financial markets, with a specific focus on agricultural commodities.
- Programming Skills: Proficiency in programming languages such as Python, R, or MATLAB. Experience with relevant quantitative libraries and tools.
- Analytical Skills: Strong analytical and problem-solving skills, with a keen ability to interpret complex data sets and develop actionable insights.
- Market Knowledge: In-depth understanding of global agricultural markets, including factors influencing supply and demand, weather patterns, and geopolitical events.