Quantitative Researcher

Overview:

Responsibilities:

• Analyze high-frequency limit orderbook data to identify patterns, inefficiencies, and predictive signals
• Build and backtest quantitative models using historical tick and orderbook data
• Collaborate with senior researchers and traders to translate research findings into production-ready strategies
• Develop and maintain data pipelines for processing large-scale, high-frequency market data
• Apply statistical and machine learning techniques, particularly tree-based methods, to improve signal quality
• Continuously monitor and iterate on live signals and models based on performance

Requirements:

• 1–3 years of professional or research experience working directly with orderbook / limit order book (LOB) data
• Technical degree/background in a quantitative field (Math, Statistics, CS, Physics, Engineering, Financial Engineering)
• Strong proficiency in Python, including standard data science libraries (pandas, NumPy, etc.)
• Genuine interest in financial markets and market microstructure — you follow markets, not just models
• Solid foundation in statistics and quantitative analysis
• Strong problem-solving skills and intellectual curiosity
• Ability to communicate technical findings clearly to non-technical stakeholders
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