Ignite your career at a top-tier high-frequency trading firm that’s reshaping the future of finance...

As a Quantitative Researcher, you will play a pivotal role in shaping trading strategies and enhancing market performance in a dynamic environment driven by innovation and cutting-edge technology. In this role, you will develop and refine cutting-edge models and algorithms that drive their proprietary trading operations, leveraging your expertise to unlock unique opportunities in a fast-paced global marketplace. Your contributions will be vital in shaping the firm’s success, and you will work alongside some of the brightest minds in the industry, pushing the boundaries of quantitative finance.

You will be responsible for tackling complex data challenges and creating proprietary models that leverage large datasets, advanced statistical techniques, and machine learning. With access to petabytes of financial data, powerful computing resources, and a dedicated GPU cluster, you will have the tools necessary to support your research and analysis. Collaboration is key, as you will work closely with traders and engineers to turn your research insights into real-time trading strategies in a competitive environment.

Key Responsibilities:

• Model Development: Design and optimise predictive models for trading across multiple asset classes, including equities, fixed income, and derivatives.
• Data Analysis & Signal Discovery: Analyse large datasets to identify trends and signals, extracting actionable insights despite high levels of noise.
• Machine Learning & Advanced Analytics: Apply a variety of statistical and machine learning techniques, from linear models to deep learning, to solve unique problems and enhance trading strategies.
• Collaborative Strategy Implementation: Partner with traders, researchers, and engineers to implement models that can adapt to rapidly changing market conditions.

Qualifications:

• Quantitative and Technical Expertise: You should hold an advanced degree (Ph.D. preferred) in a quantitative field such as mathematics, physics, statistics, computer science, or a related discipline.
• Programming Skills: Proficiency in Python for data analysis and model development is essential; experience with C++ for high-performance applications is a strong plus.
• Machine Learning Experience: Practical experience with machine learning techniques, especially in high-noise environments, is beneficial.
• Analytical Skills: You must possess strong problem-solving abilities, applying mathematical reasoning to tackle complex financial challenges.
• Collaborative Approach: Excellent communication skills and a willingness to engage with colleagues across research and trading teams are essential for success.

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