Quantitative Developer (Python)
Job details
Quantitative Developer (Python) Algorithm & Trading System Development, ML & Non-ML (3/2 Hybrid Working) Opportunity to join a leader in algorithmic trading, widely regarded as one of the top trading firms across the entire quantitative trading space, as a quantitative developer in their algorithm development team. In this team you will collaborate closely with quantitative researchers and traders to develop, implement, and optimize high-performance trading algorithms and tools (utilizing machine learning). You will work in a fast-paced, data-driven environment where the ability to problem-solve, innovate, and think critically is crucial. Types of responsibilities include (but not limited to):
- Algorithm Development: Design, implement, and optimize sophisticated trading strategies in collaboration with quantitative researchers and traders.
- System Architecture: Build and maintain high-performance, low-latency trading systems and infrastructure to support the firm’s trading activities.
- Data Analysis: Analyze and process large datasets, extracting meaningful insights to inform trading decisions and strategy refinement.
- Optimization: Continuously improve algorithmic performance and system efficiency, focusing on scalability, speed, and accuracy.
- Collaboration: Work closely with quants, traders, and engineers to understand their needs and translate them into technical solutions.
- Technology Stack: Utilize modern technologies such as Python and/or C++, and distributed systems to develop scalable, efficient solutions.
- Research & Innovation: Contribute to the development of new trading models, tools, and systems that provide a competitive edge in the market.
- Experience working in or exposure to the financial services industry, particularly quantitative trading.
- Familiarity with high-frequency or systematic trading systems and their associated challenges.
- Knowledge of multi-threading and concurrent programming, especially in a low-latency environment.
- Experience with cloud-based infrastructure or distributed systems frameworks.
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