We’re looking for a technically sharp, self-driven Quant Developer to join our client’s fast-paced trading team. This role involves hands-on research, model development, and system integration—ideal for someone who thrives on turning data into strategy and prototypes into production-ready tools.
What You’ll Be Doing:
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Design and test statistical or predictive algorithms using diverse datasets
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Own the research pipeline end-to-end—from ideation and method selection to validation, backtesting, and live performance tracking
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Ensure the quality and integrity of large data sources, identifying anomalies and cleaning as needed
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Explore new data sources for potential signal generation
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Translate research insights into robust Python-based implementations
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Contribute to the ongoing improvement of the trading infrastructure and provide support for operational enhancements
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Jump into ad hoc tasks and new initiatives as priorities shift
What We’re Looking For:
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An advanced degree (Master’s or higher) in a quantitative field like Mathematics, Computer Science, or a closely related discipline
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Minimum 3 years of hands-on experience in a similar capacity
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Fluent in Python with a solid understanding of modern programming practices and object-oriented design
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Demonstrated ability to conduct empirical research and build machine learning or statistical models from raw data
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Familiarity with optimizing and testing latency-sensitive algorithms in a Linux-based production setting
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Exposure to order book dynamics and statistical modeling related to limit order book trading
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Experience working with SQL databases and APIs to support real-time data needs and model integration
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Dependable work habits and consistent availability
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