Our client is a leading asset management firm specializing in quantitative research and trading. We utilize cutting-edge technology and advanced quantitative methods to drive profitability in the global financial markets. With a dynamic team of professionals, we are committed to innovation, excellence, and continuous growth.
We are seeking a talented and experienced Senior Quantitative Researcher to join our clients team in either London or Paris. The ideal candidate will have 3-8 years of experience in quantitative research, with a strong understanding of liquid futures and currencies markets. This individual will play a key role in developing and implementing quantitative trading strategies, conducting research, and optimizing trading algorithms.
Responsibilities:
Conduct quantitative research to identify profitable trading opportunities in liquid futures and currencies markets. Develop and implement quantitative trading strategies using statistical analysis, machine learning techniques, and mathematical modeling. Collaborate with traders, developers, and other team members to design and optimize trading algorithms. Analyze market data, perform backtesting, and evaluate the performance of trading strategies. Stay up-to-date with the latest developments in financial markets, quantitative research methodologies, and technology advancements. Contribute to the continuous improvement of research processes, tools, and infrastructure. Mentor junior team members and provide guidance on quantitative research techniques and best practices.
Requirements:
Bachelor's or Master's degree in a quantitative field such as Mathematics, Physics, Statistics, Computer Science, or Engineering. 3-8 years of experience in quantitative research or algorithmic trading within the financial industry. Strong knowledge of liquid futures and currencies markets, including market microstructure and trading dynamics. Proficiency in programming languages such as Python, R, or MATLAB for quantitative analysis and development. Experience with statistical analysis, machine learning, and mathematical modeling techniques. Familiarity with data analysis libraries (e.g., pandas, NumPy, SciPy) and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Excellent analytical and problem-solving skills, with a keen attention to detail. Effective communication skills and ability to work collaboratively in a team environment. Fluency in English; proficiency in French is a plus for the Paris location.
